LRBA, all of which can be examined further in additional studies.There remains a lack of identification of genes responsible for the most aggressive of prostate cancers. A unique resource consisting of sampled, related men who died from their confirmed prostate cancer and who were members of pedigrees shown to have a significant excess of prostate cancer cases has allowed the identification of multiple rare candidate predisposition variants for prostate cancer. Strong candidate variants are presented, including a rare, validated variant in the gene LRBA . The rare risk variant in LRBA was observed to segregate in five pedigrees. The overall predicted structures of the mutant protein do not show any significant overall changes upon mutation, but the mutated structure loses a helical structure for the two residues after the mutation. This unique analysis of closely related individuals with lethal prostate cancer, who were members of high-risk prostate cancer pedigrees, has identified a strong set of candidate predisposition variants which should be pursued in independent studies. Validation data for a subset of the candidates identified are presented, with strong evidence for a rare variant in LRBA.There is evidence for contribution of inherited factors to prostate cancer, and more specifically to lethal prostate cancer, but few responsible genes/variants have been identified. We examined genetic sequence data for 51 affected cousin pairs who each died from prostate cancer and who were members of high-risk prostate cancer pedigrees in order to identify rare variants shared by the cousins as candidate predisposition variants. Candidate variants were tested for association with prostate cancer risk in UK Biobank data. Candidate variants were also assayed in 1195 additional sampled Utah prostate cancer cases. We used 3D protein structure prediction methods to analyze structural changes and provide insights into mechanisms of pathogenicity. Almost 4000 rare (<0.005) variants were identified as shared in the 51 affected cousin pairs. One candidate variant was also significantly associated with prostate cancer risk among the 840 variants with data in UK Biobank, in the gene  ATM, BRCA1, BRCA2, CHEK2, HOXB13, MLH1, MSH2, MSH6, PMS2, and PALB2 [There is evidence for an inherited contribution to predisposition to prostate cancer, and stronger evidence for lethal prostate cancer ,3,4,5,6.nd PALB2 , not allWe sequenced germline DNA from 51 pairs of cousins who both died from prostate cancer who were also members of pedigrees with a significant excess of prostate cancer cases. We identified the set of rare coding and noncoding variants shared in these high-risk lethal prostate cancer-affected cousin pairs as strong candidate variants for predisposition to prostate cancer. Confirmation of significant association with prostate cancer risk in an independent population and observation of segregation of variants with prostate cancer in multiple high-risk pedigrees provided additional validation for a subset of the candidates considered. We used 3D protein structure prediction methods to analyze structural changes in one outstanding candidate variant that may provide insights on mechanisms of pathogenicity .The UPDB consists of the genealogy of the majority of the Utah population, from its founders in the mid-1800s to their modern-day descendants. The genealogy has been linked to the Utah Cancer Registry (UCR) and to Utah death certificates coded with International Classification of Disease causes of death from 1904. The statewide UCR was created in 1966 and has been an NCI Surveillance, Epidemiology, and End-Results (SEER) registry since 1973. It records and tracks all independent primary cancers diagnosed or treated in Utah, including pathologic confirmation. Of the over 3 million individuals with genealogy of at least 3 generations linking to Utah founders, there were 7727 individuals whose linked Utah death certificate indicated prostate cancer as a cause of death; 6328 of these individuals also had a UCR record confirming a prostate cancer diagnosis.Using the combined UPDB genealogy and UCR data, the Genetic Epidemiology Program at the University of Utah has previously identified and sampled ~2500 prostate cancer cases and ~7500 relatives who belonged to approximately 500 Utah pedigrees that each had an excess of prostate cancer cases among the descendants (high-risk pedigrees). In total, 422 of these sampled prostate cancer cases were since identified to have died from their prostate cancer based on the presence of prostate cancer as a cause of death on their linked Utah death certificate. These men were termed lethal prostate cancer (LPrCa) cases. All genetic relationships among these cases were identified in the UPDB genealogy to identify descending pedigrees.p < 0.05). For each of these high-risk prostate cancer pedigrees identified, which also contained at least 2 sampled LPrCa cases, we selected those LPrCa cases who were related as first or second cousins for sequencing. Each of the 102 LPrCa cases in the 51 cousin pairs identified had a stored sample of germline DNA extracted from whole blood available for whole-genome sequencing.All independent descending clusters (pedigrees) including 2 or more of the 422 sampled men who died of their prostate cancer (LPrCa cases) were identified in the UPDB. No pedigrees were completely overlapping, but an LPrCa case could belong to more than one pedigree through different ancestors. Each pedigree that included at least two sampled LPrCa cases was tested for a significant excess of prostate cancer cases as follows. All individuals with biological sex of male and at least three generations of genealogy linking to Utah founders were assigned to a cohort based on five-year birthyear and birth state (Utah or not). Prostate cancer cohort-specific rates were estimated as the number of prostate cancer cases in each cohort divided by the number of males with genealogy data in the cohort. Each pedigree was tested for an excess of prostate cancer cases by comparing the observed number of prostate cancer cases among the descendants to the expected number of prostate cancer cases among the descendants. The expected number of cases among the descendants was estimated by summing the cohort-specific rate of prostate cancer for all male descendants. A pedigree was termed high-risk for prostate cancer in the presence of a significant excess of observed cases (http://www.medgenome.com) utilizing 10× Genomics (https://www.10xgenomics.com/) long, linked read sequence technology. A high efficiency microfluidic device mixes functionalized gel beads containing unique barcodes with enzymes and a limiting amount of genomic DNA. These components are encapsulated in oil to produce a GEM, gel bead in emulsion. With up to 4 million barcodes available, GEM particles produce uniquely identifiable high-molecular-weight DNA fragments. These fragments are then sequenced utilizing Illumina sequencers to produce 30× whole-genome phased coverage. Genomes were aligned to GRCh37 with 10× Genomics LongRanger software version 2.2.2. VCFs were merged with BCFTOOLS. The merged VCF was annotated with ANNOVAR ([https://academic.oup.com/nar/article/38/16/e164/1749458).The 102 samples of high-molecular-weight DNA (>30 Kb in length) were whole-genome sequenced at MedGenome, Foster City, CA, USA.  coding  variants were identified in the 102 LPrCa cases. Of these, 17,859 variants had allele counts >1, and 3251 of these rare coding variants (in 1762 genes) were shared within at least 1 LPrCa cousin pair. Noncoding and UTR variants were prioritized after RegulomeDB scoring. The RegulomeDB score represents evidence that each variant functions in a regulatory role . A total of 546 rare noncoding variants with RegulomeDB scores ranging between 2a and 4, and shared in at least 1 cousin pair, were identified. https://www.illumina.com/products/by-type/informatics-products/designstudio.html). A total of 200 base pairs of genomic sequence surrounding each variant was used for the design process. Assays were manufactured for 3559 of these candidate variants (238 failed to design). Illumina iSelectHD Custom Beadchips were processed at the University of Utah HSC Genomics Core.These 3797 (3251 coding + 546 noncoding) rare, shared candidate predisposition variants were submitted for assay design using the Illumina iSelectHD Custom Genotyping BeadChips ; all other sampled prostate cancer cases whose death certificate indicated prostate cancer as a cause of death (n = 320 LPRCA cases); all sampled prostate cancer cases who were first-, second-, or third-degree relatives of the affected cousin pair cases (n = 168) and all sampled prostate cancer cases who were first-, second-, and third-degree relatives (n = 307) of these 168 cases; and all metastatic prostate cancer cases recruited by author N.A. in the Huntsman Cancer Institute Urology Clinic (n = 401). DNA for 1195 of these 1298 sampled prostate cancer cases passed quality control and was assayed for the candidate variants to test for segregation and to identify additional carriers.These rare, shared candidate predisposition variants that were identified in the sequencing experiment and had data in UK Biobank were analyzed for association with prostate cancer risk in a set of 7764 Caucasian prostate cancer cases and 1:1 ancestrally matched controls from among the UK Biobank’s 488,377 total subjects genotyped on the Illumina OmniExpress SNP array . UK Biobp < 1 × 10−5, MAF < 0.005, duplicated position in the HRC’s reference genome, or site not included in the HRC’s reference genome. The remaining 430,678 SNPs were converted to human genome B37 forward strand orientation using GenotypeHarmonizer software [2) < 0.7 [The selected UK Biobank case and control subjects were imputed to ~40M SNP markers using the Haplotype Reference Consortium’s (HRC) 67 K background genomes . Beginnisoftware  and servsoftware  and MINIsoftware . Post-im2) < 0.7 ,21. LRBA (lipopolysaccharide-responsive beige-like anchor protein) is a very large protein with 2863 amino acids that is not tractable using existing 3D structure prediction methods. The only experimental structure available for LRBA is an X-ray structure for positions 2076–2489 ,23. Therp < 0.05/840 or p < 5.95 × 10−5), in the gene LRBA .Only 840 of the 3797 candidate predisposition variants had some data present in UK Biobank, likely due to the very low frequency (<0.005). Only 1 of the 840 variants was significantly associated with prostate cancer risk after correction for multiple testing  carriers with the assay. These variants were considered to have failed performance, since the assay should have at least identified the original cousin pair carriers. For 562 of the variants, although some het carriers were identified, the assay did not identify the original cousin pair as carriers, so these variants were also considered to have failed the assay. For 78 of the variants, the only carriers identified in the assay were the original cousin pair; these variant assays were considered to have performed appropriately, but they did not identify any additional carriers of the candidate variants. This finding was not unexpected given the rare nature of the variants, but these variants did not provide any additional evidence for segregation and were not further considered here. For the remaining 884 of the variant assays, all original cousin pair carriers were identified, as well as additional het carriers. These 884 candidate variants were considered the best rare candidate lethal prostate cancer predisposition variants. These variants were examined further in the 1195 prostate cancer cases assayed, to determine if segregation to other related prostate cancer cases was observed.All het carriers for each of these 884 rare candidate variants were analyzed by identifying all genealogical relationships among the het carriers using the UPDB linked genealogy. This analysis identified many more clusters than the original 51 pedigrees analyzed since all genetic relationships among all cases were considered; 1959 total clusters (pedigrees) that included 3 or more related het carriers for at least 1 of these 884 variants were identified. Although none of these pedigrees overlapped completely, a case could belong to more than one. These 884 candidate variants were all originally selected for their low frequency (<0.005) based on review of GnomAD. However, some of the variants were observed at much higher frequency than 0.005 in the assay of 1195 prostate cancer cases. It is possible that these variants might represent truly rare variants that were observed in much higher frequencies in the assay of prostate cancer cases because they are, in fact, strongly associated with prostate cancer risk. However, these results might also be due to inaccuracies in reporting of frequencies for what were, in fact, more common variants, or due to assay performance failure. We could not confirm the lack of a data problem for these more commonly observed variants, so we elected to exclude consideration of any of the 1959 variant-segregating pedigrees for any variant for which more than 10% (n > 110 carriers) het carriers were observed in the assay of 1195 prostate cancer cases. p < 0.05) among the descendants of the common founding ancestor of all the related carriers. This left 814 high-risk prostate cancer pedigrees, including 559 different rare candidate variants in 398 genes that showed evidence of segregation of the candidate variant with prostate cancer. The list of these 559 rare candidate predisposition variants is provided in This left 1070 pedigrees of interest that included at least 3 related het carriers of 1 of the candidate variants. Because some of these clusters of het carriers might represent random clusters rather than high-risk prostate cancer pedigrees, we additionally excluded those variant-sharing pedigrees that did not exhibit a significant excess of prostate cancer cases (LRBA). This LRBA variant (rs62346982) is classified in ClinVar with “conflicting interpretations of pathogenicity”. The LRBA variant was observed to segregate with prostate cancer in a total of five high-risk prostate cancer pedigrees. LRBA variant in the largest LRBA-segregating pedigree identified. The founder of this pedigree was born in the late 1700s in Vermont and has almost 32,000 descendants in UPDB, with a total of 230 prostate cancer cases observed and 174.9 expected (p = 4.0 × 10−5) among all descendants ; variant-carrying cases are shown. A multiple marriage in the third generation is noted with a triangle on the two horizontal marriage lines, variant carriers are noted by “+”, and the decade of prostate cancer diagnosis is noted below each case. It must be noted that complete prostate cancer case diagnosis data for Utah are only available from 1973, which explains why cases are only observed in the bottom, most recent few generations of the high-risk pedigrees shown.Only 1 of these 559 candidate variants was significantly validated for risk association with prostate cancer (LRBA), the single candidate predisposition variant identified in a cousin pair and also confirmed with significant association to prostate cancer in the UK Biobank case/control analysis, is involved in coupling signal transduction and vesicle trafficking to enable polarized secretion and/or membrane deposition of immune effector molecules (this function was assigned by similarity). It is involved in phagophore growth during mitophagy by regulating ATG9A trafficking to mitochondria. A mutation of this protein has been associated with CVID8, an autosomal recessive immunologic disorder associated with defective B-cell differentiation.Lipopolysaccharide-responsive and beige-like anchor protein (The variant considered here corresponds to rs62346982. PolyPhen-2 predictor predicts this variant as benign with a score of 0.167 (sensitivity 0.92 and specificity 0.87) . The oveLRBA variant as a strong candidate prostate cancer predisposition variant, this study identified a large set of other rare candidate predisposition variants, many of which are worthy of further consideration. We have used various criteria to select a subset of these LPrCa candidate predisposition variants for presentation in more detail below. These criteria include: (i) known cancer pathogenic variants, (ii) variants in genes recognized to be implicated in breast cancer (BROCA genes), and (iii) noncoding variants with suggestive Regulome DB scores.In addition to the significant evidence identifying the rare (i)Cancer pathogenic variantsMUTYH (seq_1_45797228_C-T_MUTYH). This variant was identified in 29/1195 of the assayed cases and segregated in 3 high-risk prostate cancer pedigrees including 6, 3, and 3 sampled related cases, respectively. p = 2.7 × 10−7). The founding male had two marriages, indicated with a small triangle on the top horizontal marriage lines.Only one candidate variant that was classified as “pathogenic/likely pathogenic” in ClinVar was identified, in DUOX2, LRBA (discussed previously), MYO3A, EVC, CP, FBN1, MYH11, KCND3, ACNT2, ADAM9, and PTCH1. The largest pedigree observed for the “conflicting” variant identified for DUOX2 (n = 14 case carriers) is shown in LRBA (n = 10) was shown in PTCH1 was also selected as a BROCA gene, and a pedigree is shown later. A variant in MSH6 was the only variant of 14 classified in ClinVar as of “uncertain significance” that also reported a cancer-related clinical diagnosis; it was also selected as a BROCA variant and is shown later.Eleven candidate variants found to segregate in high-risk pedigrees were classified with “conflicting interpretations of pathogenicity” in ClinVar; these included variants in DUOX2 variant in a high-risk prostate cancer pedigree. The founder of this pedigree was born in the mid-1700s in North Carolina and has almost 153,000 descendants in UPDB; 897 prostate cancer cases were observed among all descendants, with 811.5 expected (p = 0.0016). The male founder of this pedigree had two spouses, shown with a triangle on the top horizontal marriage lines. All 14 prostate cancer case variant carriers are shown with “+”, and 1 inferred case (father of an affected carrier who was not sampled) is also shown.(ii)Variants in recognized BROCA genesMUTYH variant already discussed, as well as variants in APC (ClinVar: conflicting interpretations of pathogenicity), BRCA1 (benign), MSH6 (uncertain significance), PTCH1 (conflicting), SDHC (not classified), and SLX4 (benign/likely benign). The pedigrees segregating the rare variants in BRCA1, MSH6, and PTCH1 are shown in Seven of the rare candidate predisposition variants found to segregate in prostate cancer cases who were members of high-risk prostate cancer pedigrees were in known BROCA genes, including the BRCA1 variant (seq_17_41228587_T-G_BRCA1). This variant has been classified as “benign” in ClinVar, based on the breast cancer phenotype. The founder of this pedigree was born in the early 1800s in Canada and has a total of over 2300 descendants in the UPDB; a total of 25 prostate cancer cases were observed among all descendants, with 12.1 expected (p = 7.6 × 10−4). The three identified variant carriers are shown with “+”; also shown is the unsampled pedigree member father of one of the affected pair cases who was also diagnosed with prostate cancer. This pedigree also has a significant excess of breast cancer . There are no identified breast cancer-affected descendants of the first son of the founder pair shown in MSH6 variant (seq_2_48026979_A-C_MSH6). This variant is classified as “uncertain” in ClinVar. The founder of this pedigree was born in the early 1800s in Massachusetts and has almost 23,000 descendants in UPDB; 166 prostate cancer cases were observed among all descendants, with 113.0 expected (p = 1.8 × 10−6); 129 breast cancers were observed with 109.8 expected (p = 0.04); 23 ovarian cancers were observed with 13.9 expected (p = 0.016). Neither colorectal nor endometrial cancers were observed in excess among the descendants in this pedigree. Prostate cancer case variant carriers are shown with “+”; one unsampled father of a carrier was also diagnosed with prostate cancer as shown. Two of the prostate cancer case carriers had an additional cancer diagnosis in UPDB (one kidney and one chronic lymphocytic leukemia); data are not shown to protect privacy.PTCH1 variant (seq_9_98240378_C-T_PTCH1). This variant is classified as “conflicting” in ClinVar. The founder of this pedigree was born in the mid-1800s with no recorded birthplace and has almost 4600 descendants in UPDB; a total of 33 prostate cancers were observed among all descendants, with 20.0 expected (p = 0.0047). This pedigree also exhibits a significant excess of breast cancer: a total of 37 breast cancers were observed in the entire descending pedigree, with 23.1 expected (p = 0.0045). One of these breast cancer cases was the mother of a carrier, shown with half shading.(iii)Noncoding variants with suggestive Regulome DB scoresPAX6 and ZWILCH, and both were scored “2a”. Two pedigrees with the PAX6 variant were observed with three het carriers each, and one pedigree with the ZWILCH variant also included three het carriers; these pedigrees are not shown. Regulome DB (RGDB) scores ranging from “2a” to “4” were observed among the rare candidate variants. The two variants with the most evidence for a regulatory role based on RGDB score were in APCDD1L-DT variant with score “2b”, was born in the late 1700s in Massachusetts and has over 36,000 total descendants, with 268 prostate cancer cases observed among all descendants, and 167.8 expected (p = 6.6 × 10−13). Multiple variants with an RGDB score of “2b” were identified, but pedigrees are not shown here. The founder of the largest pedigree, with 11 het carriers of an It is estimated that 10–20% of prostate cancer cases occur in a familial context . GeneticHigh-risk pedigree studies remain a powerful mechanism for identification of predisposition genes and variants ,32,33,34GOLM1 for melanoma [ERF for bladder cancer [FANCM for colorectal cancer [MEGF for osteoporosis [HOXC4 for Chiari Malformations [Extensive linked genealogic and disease registries existing in Utah have been used to identify and study thousands of Utah high-risk pedigrees . We havemelanoma , ERF forr cancer , FANCM fl cancer , MEGF fooporosis , HOXC4 frmations , and mulrmations  and excermations , among oUsing the combined genealogy and cancer registry resource in the UPDB, the strongest evidence for an inherited contribution to prostate cancer has been shown for the subset of lethal prostate cancer cases . The preLRBA, was the only candidate predisposition variant to be further validated in the independent UK Biobank population for association with prostate cancer risk; this variant was found to segregate in five independent Utah high-risk pedigrees. While protein prediction modeling for this variant did not show any significant changes, the mutated structure does lose a helical structure two residues after the replacement  demonstrates the power of this approach and serves as validation of this approach to identify both known and new predisposition variants.While not all the thousands of rare, shared candidate prostate cancer predisposition variants identified in this study have been reviewed in detail due to limitations of time and space, several specific subsets of variants were presented in more detail. Subsets considered included known cancer pathogenic variants, BROCA genes, and noncoding variants with suggestive Regulome DB scores. The identification of multiple strong candidate variants in these subsets, some of which represented more than one subset (e.g., The strengths of this study include the large number of affected cousin pairs analyzed, leading to many rare, shared candidate predisposition variants being identified. Strength also comes from the analysis of the phenotype of lethal prostate cancer in the proband pairs, which was confirmed both by a linked Utah death certificate for prostate cancer and validation of the cancer diagnosis within the linked Utah Cancer Registry. The available stored germline DNA from thousands of Utah prostate cancer cases, many of whom were related to the affected cousin pairs sequenced, allowed further validation of candidate variants by the confirmation of segregation of the variants. Limitations of this study include the censoring of some death, cancer, and genealogy data, which may have occurred through errors of reporting or record linking, or through lack of records. Also of note is that the founding population of Utah is largely northern European , and whiBRCA1 and BRCA2 [CDKN2A [Analysis of high-risk cancer pedigrees identified in this powerful Utah resource previously provided the identification of nd BRCA2 ,49, and  [CDKN2A , which r [CDKN2A . Whether


The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage  of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson’s disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson’s disease.The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson’s disease has formed the backbone for a proposed staging system for incorporation in Parkinson’s disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson’s disease patients into trials (as distinct from patients with non-Parkinson’s disease parkinsonism or non-Parkinson’s disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson’s disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer’s disease-like pathology (detectable through CSF levels of amyloid-β Vijiaratnam and Foltynie consider how fluid and imaging biomarkers can best be used in Parkinson’s disease trials to help select participants most likely to benefit from candidate disease-modifying agents, confirm target engagement, and track disease progression and treatment response. Despite decades of trials evaluating promising candidates, no treatments have yet been proven to achieve this. While this may be due to lack of trial evaluation of truly effective agents, other potentially contributing factors include imprecise patient selection, inadequacies in trial design, failure to confirm target engagement and the absence of objective measures of disease progression.2 An ideal biomarker should be readily quantifiable in accessible clinical samples , while being reliable, quick and inexpensive.One way of improving the likelihood of success is by identifying better biomarkers. A biomarker is a characteristic that is objectively measured and evaluated from any substance, structure or process that can be measured in the body or its products as an indicator of normal biological or pathogenic processes, or pharmacologic responses to a therapeutic intervention.3 The accumulation and interplay of these abnormal protein forms with the organelles/cellular pathways involved in their clearance as well as normal cellular maintenance and survival results in neuronal dysfunction and ultimately axonal injury and neuronal death.Suboptimal patient selection in disease modifying trials may be related to poor diagnostic accuracy. Pathological modification  of the physiological protein α-synuclein (α-syn) to misfolded oligomeric and fibrillary forms is the most consistent pathological feature of PD.4 further confirming pre-existing evidence for its use,5–11 and is now proposed as a core aspect of a potential staging system for PD.13 This is potentially a pivotal step in clarifying eligibility criteria for inclusion in trials and distinguishing PD patients from those with atypical forms of parkinsonism. While needing further clarification, the α-syn SAA is at the present time largely a binary measure simply indicating the presence/absence of the pathophysiological process of α-syn aggregation and cannot yet be used to track disease severity, which instead relies on clinical measurements.The α-syn seed amplification assay (SAA) has high sensitivity and specificity for PD diagnostic accuracy, with a recent study of >1100 samples from the Parkinson’s progression markers initiative (PPMI) cohort14 be limited by reduced compliance, recall bias and fatigue,15 sometimes do not correlate sufficiently with quantitative objective assessments17 and vary in their sensitivity at different disease stages,19 raising questions about the inclusion of patients who may have progressed beyond the salvageable period.As such, there is still a need for additional biomarkers that might enrich treatment arms for PD subgroups most likely to respond and allow early exploratory analyses according to engagement of the therapeutic with its putative target. Current trials typically rely on clinical end points with scales and questionnaires, which are subject to inter-rater variability, while potentially being confounded by symptomatic drug effects. Evaluations using scales may also be compromised by non-linear changes over time,Biomarkers that are robustly demonstrated to track disease progression and treatment effects could potentially shorten periods of assessment and reduce the number of patients required for preliminary demonstration of efficacy. Ideally, short-term changes in the biomarker should anticipate long-term clinical outcomes. Furthermore, by confirming target engagement according to the dose(s) of the agent under study, biomarkers can be used to improve the distinction between an intervention’s disease-modifying effects and purely symptomatic improvements. While there are parallel efforts exploring additional biomarkers for PD prior to clinically manifest disease, in this review, we will discuss the current state of fluid, tissue and imaging biomarker developments in clinically established PD and their potential for use either alone or in combination in future disease modifying clinical trials.Box 1ELISAtarget-specific antibodies bind to the sample proteinssecondary antibody linked to an enzyme recognizes the matched antibodiesfluorescent reaction is created when exposed to a chemical substrateamount of antigen present correlates to intensity of colour changedetection range inferior to other high-sensitivity techniquesLuminexbeads conjugated with antibody against specific analyte present different colour codeshigh-throughput screeningcan measure up to 80 different proteins or RNA from a single microplateMesoscale discoveryhigh-throughput measurement of single or multiple targetsantibodies can be conjugated to generate electro chemiluminescent signals, unlike ELISASingle molecule arrayantibody-based ELISA and bead-based platformantibody-coated bead binds to a single molecule and analysed separatelymultiplexing of up to 11 analytes, high sensitivity and wide detection rangeProximity extension assayDNA oligonucleotide tags linked to matched antibodies that both bind to target proteinantibodies come into proximity on binding, DNA duplex formed, sequence amplifiedwide library of matched antibodies with high sensitivity and specificity for their targetsSomaScanAptamers  bind targetquantified by microarrays or quantitative PCRallows creation of library with high sensitivity for targetsSingle molecule countingantibody–antigen sandwich complexes from either beads or platesbroken up and fluorescently labelled detection antibody counted by laser beamallows for a high dynamic concentration rangeMass spectrometrymeasures mass-to-charge ratio of one or more molecules presentprovide quantitative information about composition of complex protein samplescan also provide information about conformational propertiesMicroscopyused to examine to structure and formation of aggregatesapproaches include fluorescence (aggregates labelled with fluorescent probes) microscopy and electron microscopy (resolve oligomer structure at higher resolution)Seed amplification assaysaggregation assays that detect the presence of protein aggregatessample sonication and incubation with recombinant protein monomeraggregate seeds template and induce aggregation of the excess protein monomersreaction monitored by a thioflavin readout, aggregation curve characteristics recordedExtracellular vesicles protein measurementreleased by cells, content represent central nervous system processesprecipitation to increase concentration and neuronal enrichment with immune captureprotein quantification with electrochemiluminescence Total, phosphorylated and oligomeric α-syn levels and their ratios in CSF, blood and other body fluids and tissues have all been explored for biomarker use .21–30 Measurement of total α-syn levels in extracellular vesicles (EVs) either in CSF,31 plasma/serum32–39 or saliva40 can distinguish PD from controls.41–43 Total α-syn levels in EVs derived from neurons can also distinguish PD from atypical disorders, though best distinction is achieved when α-syn levels are combined with levels of other proteins such as clusterin.44 Similarly, differences in α-syn levels in neuronal- compared with oligodendroglial-derived EVs shows promise for distinguishing PD from multiple system atrophy (MSA).38 Phosphorylated α-syn at serine-129 (Ser-129p-α-syn) levels are elevated in the CSF,45–48 serum and plasma49–52 of PD patients, although similar elevations are seen in atypical parkinsonian conditions, limiting specificity/diagnostic use.53–56 Elevated levels are similarly seen for Ser-129p-α-syn in skin.57–61 A predilection for Ser-129p-α-syn deposition in autonomic compared with somatosensory nerve fibres and proximal to distal gradients could be applied for improving the distinction between PD and MSA-parkinsonian type (MSA-P).63Total free α-syn levels have been explored in CSF, plasma/serum, saliva and submandibular gland tissue and are of no diagnostic value in PD.64–68 plasma,70 red blood cells,72 saliva and tears73–78 of PD patients . Oligomeric CSF α-syn levels taken alone, however, have unsatisfactory diagnostic properties.25 Combining oligomeric α-syn and aggregated tau measurement in serum neuronal-derived exosomes seems to distinguish PD from tauopathies well.81 Reliable quantification and differentiation approaches between protein species  are currently lacking.53 Making these distinctions will be critical in improving the diagnostic performance of aggregated forms, considering unique patterns have been noted in different synucleinopathies.83 Ratios of Ser-129p-α-syn and/or oligomeric α-syn to total α-syn are elevated in PD and seem most promising in overcoming the limitations of individual markers for differentiating synucleinopathies.85Levels of α-syn oligomers are also increased in the CSF,86–88 Studies comparing brain and CSF samples have demonstrated excellent performance for distinguishing PD from healthy controls (sensitivity and specificity: 90–100%),4–11 with comparable results for both seeding methods10 across laboratories.10 Assays can also distinguish PD from non-synuclein disorders such as progressive supranuclear palsy (PSP) and corticobasal syndromes (CBS),11 although the accuracy in distinguishing MSA from these conditions is poor (sensitivity: 4–82%), while studies exploring the use of α-syn SAA to distinguish MSA from PD have also reported variable findings.87–91 As differences in α-syn strains and therefore biochemical, morphological and structural properties of the final α-syn SAA reaction products underlie PD and MSA phenotypic heterogeneity, different outcomes may be explained by the fact that different chemical environments (SAA reaction mixes) can differentially influence the formation and growth of different strains. Protocols optimized for PD may not therefore work so well for MSA detection.92Seed amplification assays such as real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) are arguably the most important achievement in the field of biomarkers to date and will likely be the most useful diagnostic biomarker for trials. These techniques can amplify and detect minute amounts of aggregated α-syn in CSF.93 while aggregation rates using RT QuIC correlate with cognitive and motor status.8 Similarly, seeding activity in submandibular gland tissue of PD patients has been noted, although sensitivity (73.2% versus 100%) and specificity (78.6% versus 94%) for distinguishing PD from healthy controls varies between studies,95 while preliminary findings in saliva are promising.96 A recent report demonstrating the excellent ability of serum immunoprecipitation-based RT-QuIC for distinguishing PD from healthy controls may herald a new approach to diagnosing PD via a simple blood test, although lower detection rates in MSA, likely due to technical factors, will still need to be overcome.97 Similarly, the demonstration of seeding activity from pathological α-syn derived from plasma EVs is also promising.98 The use of less invasive samples will be ideal for trial recruitment (given feedback from patients regarding tolerability of submandibular gland biopsy) but will require demonstration of comparability with the high sensitivity and specificity achieved with CSF .In attempts to avoid lumbar puncture, the use of α-syn SAA has been explored using samples obtained through less invasive approaches. Increased α-syn skin seeding activity has been observed in PD (post-mortem and living) patients with excellent distinction from non-neurodegenerative cases,49 EV total α-syn levels also predict and track progression in PD poorly.100Total free α-syn levels do not correlate with disease severity and their ability to predict and track progression is also poor.101 and motor symptom progression,102 an inverse relationship in later disease 103 makes its use as a progression biomarker challenging if applied to trials with long-term follow-up or involving patients with established disease. CSF and serum levels of a number of other phosphorylated α-syn species have also been explored, although preliminary findings are somewhat conflicting.104–106 A rostro-caudal pSer129-α-syn deposition gradient in the gastrointestinal tract of PD patients has also been noted, reflecting neurodegeneration in the myenteric plexus,108 although this may be a reactive physiological phenomenon.109 Disentangling reactive from pathological components will be important, as deposition may occur here earlier and therefore guide earlier treatment in early motor stages where diagnostic criteria have yet to be totally fulfilled.While Ser-129p-α-syn levels do seem to reflect disease severity103 despite some contradictory evidence,110 although previously highlighted limitations of differentiating aggregated forms need to be addressed. Longitudinal measurement of Ser-129p-α-syn and/or oligomeric to total α-syn ratios might detect effective treatment responses.101 Similar findings have also been observed when measuring these ratios in serum and salivary EVs, although this does not seem to offer additional value.112Oligomeric CSF α-syn levels can also reflect PD severity and progression,113 Taken together, the best α-syn candidate biomarkers for diagnosing PD to consider for clinical trials are α-syn SAA. The ratios of Ser-129p-α-syn and or oligomeric α-syn to total α-syn can also helpfully differentiate between synucleinopathies84 and are credible markers for tracking progression.Correlation of α-syn SAA with disease severity and progression is unclear, and specific kinetic cut-offs remain elusive, although quantification of α-syn SAA end products with oligomer-specific enzyme-linked immunosorbent assay (ELISA) may be helpful in this regard.42 and Aβ40, which can form extracellular amyloid plaques.115 Tau proteins comprise highly soluble isoforms, while their hyperphosphorylation contributes to the development of neurofibrillary tangles (NFTs).116 Amyloid plaques are abundant in the CNS alongside NFTs in Alzheimer’s disease (AD), while NFTs are characteristic of PSP and CBS.118Amyloid-β (Aβ) peptides are cleaved from the amyloid precursor protein (APP) into the peptides Aβ42 and Aβ40). Higher CSF t-tau and decreased Aβ42 levels occur in tauopathies. This combination best distinguishes PD from CBS, although the relative rarity of CBS makes widespread testing in PD trials of modest value.120 Preliminary evidence suggests that ultrasensitive tau SAA may identify/exclude patients with tauopathies from PD at trial recruitment,121 although a combined assay with α-syn would be more ideal.Biomarkers reflecting tau and amyloid pathology can be measured in CSF and blood and include free and EV levels of total tau (t-tau), phosphorylated tau (p-tau) and amyloid peptide isoforms  and dementia with Lewy bodies (DLB).123–125 CSF AD-like biomarkers may, therefore, be useful for differentiating DLB from other parkinsonian disorders, although for some interventional trials this distinction may be somewhat arbitrary. Levels of t-tau and p-tau are increased in all parkinsonian disease groups and combining them with Aβ42 only usefully differentiates PD from frontotemporal dementia.126 Taken together, these findings suggest free blood levels of these markers are unlikely to be of diagnostic value in trials.The combination of reduced Aβ127 and correlate with an acceleration in cognitive decline.129 PD patients with lower CSF Aβ42 levels at disease onset also have earlier appearance of cognitive impairment and more rapid conversion to PD-related dementia.131 The measurement of CSF Aβ42 could, therefore, be of prognostic value by reflecting brain amyloid content even prior to apparent clinical cognitive impairment.132Tau and AD pathology commonly coexist in synucleinopathy patients42 and tau can also be measured in blood, levels correlate poorly with cerebral pathology,133 potentially due to extra-cerebral sources such as platelets. Ultrasensitive immunoassay technologies such as immunomagnetic reduction (IMR) improve this,134 although correlation with cognitive function has been inconsistent.136 Similarly, total tau protein blood findings have been variable,136 potentially due to rapid changes in blood concentrations,137 although higher t-tau levels seem to correlate with lower cognitive performance.138Although Aβ42 and tau can also be detected in EVs. While also not of diagnostic value, elevated levels in combination with elevated α-syn140 and lower serine phosphorylated insulin receptor substrate (IRS-p312), a marker of neuronal insulin resistance in blood EVs,141 predict worse motor and cognitive dysfunction progression phenotypes well. Larger replication studies of Aβ and tau in EVs are needed to better assess their validity for predicting cognitive dysfunction in PD before adoption for widespread use.Aβ142 P-tau181 levels have been studied in PD, and their ability to predict disease severity and cognitive decline has been mixed and, therefore, they cannot currently be recommended for trial use.143–145 Other tau species also show promise in AD and need further exploration in PD cohorts.Measurement of other phosphorylated tau species  in CSF and plasma can discriminate AD patients from cognitively unimpaired subjects and reflect cognitive measures and progression.146 Measurement of cellular components and levels of inflammatory mediators have, therefore, been explored for biomarker purposes  and MCP-1 (monocyte chemoattractant protein-1) are increased even further in atypical parkinsonian patients compared with PD and can thus reliably discriminate tauopathies from synucleinopathies,150 although this is best achieved by combining them with a panel of non-inflammatory CSF biomarkers [area under the curve (AUC) = 0.95].151 Among PD patients, GFAP levels seem to predict the development of dementia.152Immune cells in the CNS and in the periphery are involved in PD neurodegeneration.purposes . Glial 153 as is the proinflammatory lymphocyte profile (diminished T-regulatory and increased T-helper cell levels).154–157 The NLR has been negatively associated with presynaptic radionuclide striatal-binding ratios and positively associated with motor impairment,159 while a proinflammatory lymphocyte profile shift is associated with more severe motor and cognitive impairment,161 and an increase in Tregs expressing CD49d is linked to lesser motor impairment.162 Altered lymphocytes lead to and are in turn influenced by cytokines. Elevated C-reactive protein (CRP), interleukin (IL)-6 and IL-10 as well as tumour necrosis factor α and chemokine ligand 5  levels have been noted in PD.163–171 Current evidence does not, however, suggest these markers would help in distinguishing PD from atypical conditions considering inconsistent findings between studies172–174 and small-to-intermediate effect sizes.175 Similarly, associations with non-motor symptoms noted particularly for IL-6 and IL-10176 are unlikely to be of value for trial design, although associations of pro-inflammatory cytokines, particularly CRP and CCL5, with reduced survival177 and the development of motor and cognitive impairment178–180 are of value for both prognosis and monitoring progression.Neutrophil-to-lymphocyte ratios (NLRs) are indicative of overall inflammatory status and are elevated in PD compared with healthy controls181 While better validated general biomarkers of progression exist, these panels could be particularly useful for enriching trials that test agents targeting inflammatory pathways.Taken together, the value of individual inflammatory markers is low, although combining several inflammatory markers to predict disease progression will likely contribute to future approaches.182 while the phenotype, pathophysiology and α-syn SAA findings and post-mortem pathology can also be completely different, despite the same LRRK2 mutation.183 The far lower rates of positivity of the CSF α-syn SAA among LRRK2 mutation carriers questions whether these patients should be included within trials specifically targeting α-syn and potentially other broad interventions being considered for PD neurodegeneration.184 Nevertheless, there is great interest in targeting LRRK2 as a means of influencing disease progression in PD, and genetic status may be of greater relevance for these interventions than other biomarkers. That said, the most advanced LRRK2 inhibitor trial has pragmatically chosen to focus recruitment of a combination of PD patients with and without LRRK2 mutations (NCT05348785), while other LRRK2-specific interventions may specifically want to recruit the subgroup who are positive for the α-syn SAA.The relationship between genetic risk factors for PD and the pathophysiological processes underlying PD are under renewed scrutiny based on the use of α-syn SAA in CSF. People with leucine-rich repeat kinase 2 (LRRK2) mutations may develop typical PD, positive α-syn SAA in CSF and typical PD pathology at post-mortem,LRRK2 also occur, and these are being explored as biomarkers in trials targeting this enzyme. pS1292-LRRK2 levels are higher in urinary EVs in idiopathic PD and correlate with motor severity.185 Furthermore, CSF EV pS1292-LRRK2 levels are 10-fold higher than urinary EV levels, suggesting relevance for CNS activity.186 Genetic variability may, therefore, be considered when selecting patients for precision medicine interventions as well as for helping to balance trial arms for progression or adjusting for baseline differences in longitudinal analysis. pS1292-LRRK2 levels or other downstream molecular abnormalities  may become useful tools for measuring target engagement and the therapeutic response to agents specifically targeting these pathways, as has been demonstrated in a recent early stage LRRK2 inhibitor trial187  and glucosidase beta acid 1 (GBA1) PD patients have accelerated cognitive189–193 and motor deterioration,194 although this may be constrained to specific mutations/polymorphisms.195–197 Polygenic risk scores for predicting the rate of progression appear promising but need replication.199Other genetic factors can also determine phenotypic severity and progression. PD patients with the A53T α-syn mutation experience worse autonomic and cognitive deterioration,201 and supported by known involvement of these miRNAs in PD pathogenic processes. Sampling, quantification and analysis approaches need to become standardized to facilitate between study comparisons. SncRNA analysis from CSF EVs may also be worth further exploration.202 While plasma EV miRNA measurement appears useful when distinguishing PD from healthy controls [AUC 0.85 (miR331-5p) and 0.90 (miR-505)203], the combination of miR153 and miR-409-3p using the CSF EV approach is even more impressive (AUC 0.99).204 miRNAs may likely play a diagnostic role in future trials depending on the mode of action of the drug being studied.Non-coding RNAs (ncRNA) contribute to gene expression regulation. Micro RNAs (miRNAs) are small ncRNAs (sncRNAs), which have been explored for biomarker potential. Unique serum miRNA patterns comprising upregulation (miR-6836-3p and miR-6777-3p) and downregulation  have been noted in PDGBA1 gene encodes the lysosomal enzyme β-glucocerebrosidase (GCase). GBA1 mutation carriers have almost uniformly positive α-syn SAA in CSF.4 Impaired GCase and other lysosomal enzyme activity [e.g. cathepsin D (CTSD)] in GBA1-carrier and non-carrier PD patients leads to lysosomal dysfunction, thus negatively impacting α-syn degradation.206 Although CSF GCase activity depends on the specific GBA1 mutation carried, levels are also lower in idiopathic PD patients compared with controls.207 GCase levels are, however, of low value for diagnosing PD, although combining GCase activity with oligomeric/total α-syn ratios , as well as other lysosomal enzymes (CTSD and β-hexoxaminidase) and Aβ42, improves this .208The 209 while activity also seems to predict subsequent development of dementia regardless of genetic status.210 CSF GCase levels may, therefore, usefully allow enrichment of clinical trial arms testing agents targeting this enzyme (even in the absence of a GBA1 mutation) as well as a method for confirming target engagement. Blood GCase activity is also reduced compared with healthy controls, although prediction of progression has not been explored.212 GCase activity has been used as an exploratory outcome in recent disease modification trials in conjunction with its downstream hydrolytic product glucosylceramide , PTEN induced kinase 1 (PINK1) and the protein deglycase (DJ-1) gene, which encode proteins that mediate mitophagy, supports this link.217 Typical α-syn pathology is less consistently reported in people with these mutations, and the rate of positivity of the α-syn SAA in CSF is also low,184 thus reinforcing the potential importance of both genetic testing and selection of additional other biomarkers during trial recruitment and follow-up, depending on the mode of action of the agent being tested.Mitochondrial dysfunction contributes to the pathogenesis of PD.219 compared with controls and correlate with disease severity,21 although similarities with other parkinsonian syndromes make its diagnostic use unlikely.221 Similar poor diagnostic value has been noted for serum and plasma DJ-1 levels.222–224 Other less well studied biomarkers include phosphorylated ubiquitin at the serine 65 residue (pSer65Ub), which occurs by virtue of the loss of mitochondrial membrane potential triggering the stabilization of PINK1 at the outer mitochondrial membrane.225 While increased pSer65Ub levels have been observed in PD post-mortem brains, lower levels have been identified in familial PD with PINK1/parkin mutations.227 Investigations of this marker in biofluid samples will be of interest, possibly as confirmation of target engagement and longitudinally to assess progression rates of disease in these PD subtypes. Similarly, the peroxisome proliferator-activated receptor γ coactivator 1 alpha (PGC-1α) has been of interest due to its role as a regulator of mitochondrial function.228 The PGC-1α reference gene and PGC-1α levels are downregulated in human brain and blood leucocytes in PD compared with control patients, and this negatively correlates with disease severity.229–231 Interventions targeting mitochondrial processes might usefully measure peripheral levels of PGC-1α.The best explored mitochondrial biomarker in this context is CSF DJ-1, levels of which are decreased in PD233 This is supported by a recent study showing negligible diagnostic value for well-established biomarkers of mitochondrial disease such as fibroblast growth factor 21 and growth differentiation factor 15 in reflecting mitochondrial dysfunction in PD patients.226A concern, however, for the use of mitochondrial blood-based biomarkers is that they do not recapitulate ‘neuronal’ mitochondrial dysfunction. Genetic mutations leading to mitochondrial dysfunction in PD often show tissue-specific expression patterns, and therefore peripheral blood changes may lack interpretability.234–237 Faster progression appears to be independent from the existence of vascular disease in the brain238 and at least in part explained by disruptions in physiological brain insulin signalling 239 contributing to neurodegeneration.240The coexistence of type 2 diabetes mellitus (T2DM) with PD results in more rapid motor and cognitive progression.241 Elevated IRS-1 phosphorylation at serine positions 616 (IRS-1 p-S616) and 312 (IRS-1 p-S312) represents attenuated insulin signalling243 and has been noted in plasma EVs of PD patients.245 Decreased IRS-1 p-Tyr distinguishes PD patients from healthy controls and predicts cognitive impairment and motor severity.141 Increases in EV IRS-1 p-Tyr were associated with motor benefits from exenatide in a clinical trial, while increases in downstream p-Akt S473 predicted treatment response . Tyrosine IRS-1 phosphorylation (IRS-1 p-Tyr) evokes insulin responsiveness, while serine phosphorylation primarily deactivates IRS-1 and attenuates insulin signalling.response .244246 The mechanistic importance of these finding in PD remains unclear, as the HOMA-IR is not associated with cognition or motor symptoms.248 Abnormal range HbA1c levels, however, predict motor and cognitive severity and progression in PD, while also being associated with the degree of axonal damage.249–252 Further exploration of insulin resistance and/or body mass index in the selection of patients for trials of agents that mechanistically target this pathway is clearly of potential importance, while measurement of central insulin resistance using exosome IRS-1 p-Tyr may turn out to be of utility in confirming target engagement for a growing number of agents currently being studied for disease modification.253Peripheral insulin resistance as defined by a Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) value ≥ 2.0 or glycated haemoglobin (HbA1c) concentration ≥5.7%, occurs in up to 60% of PD patients.254 Proteins at different levels of this process have been explored for biomarker use (254–260 and markers of synaptic plasticity  in PD, inconsistencies between studies and poor correlation with motor severity and cognitive progression make future utility unlikely.261–268Disruptions to vesicle-mediated trafficking and secretory pathways with downstream effects on neurotransmitter levels and signalling as well as synaptic plasticity are key features of synucleinopathies.rker use . Evidenc270 Similarly, preliminary studies suggest CSF levels of the excitatory-inhibitory regulatory protein, neuronal pentraxin-2 (NPTX2)270 and the glutamate receptor GluA3262 suggest value in reflecting cognitive status and distinguishing PD from DLB271 and thus warrant further exploration in the assessment of cognitive progression.CSF concentrations of the secretory granule proteins (VGF and secretogranin-2) and the dense core vesicle protein prodynorphin are potentially useful in distinguishing PD from DLB or predicting cognitive decline.272 An example of this approach includes combining CSF and serum EV levels of the principal components of the soluble N-ethylmaleimide sensitive factor attachment protein (SNARE) complex  with oligomeric α-syn to improve diagnostic accuracy.263 Similarly, combining CSF Ng, NPTX2, total α-syn and age273 or CNTN-1, total α-syn, total tau, phosphorylated tau and Aβ1-42261) can also improve diagnostic distinction.Measuring panels of CSF protein levels reflecting neurotransmitter secretion, synaptic plasticity and autophagy will likely shape any future use of these markers.274–279 repeated measurements in the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study did not suggest usefulness for monitoring progression. Simultaneous metabolite panel measurement of dopaminergic , noradrenergic  and serotonergic [e.g. 5-hydroxy-3-indoleacetic acid (5-HIAA)] metabolites in CSF,278 however, correlates better with motor severity and dopamine transporter single-photon emission computed tomography (DAT-SPECT) uptake,281 and utility of the panel as a progression marker needs to be further explored.A similar approach would also be worthwhile when considering the use of neurotransmitter metabolites. Despite decreased CSF levels of the dopamine metabolite homovanillic acid (HVA) being consistently noted in PD,282 Neurofilament subunits are released upon axonal injury irrespective of the cause.282 The neurofilament light chain (NfL) subunit is of diagnostic value in degenerative parkinsonian syndromes,283 while also correlating with nigrostriatal degeneration and greater reductions in presynaptic putaminal DAT ratios over time.285 This said, CSF NfL concentration does not seem to be increased in early PD,286 and significant increases are more indicative of atypical diagnoses than PD.286–288Neuro-axonal damage represents the end event in the pathophysiology of PD. Axon cytoskeletons are comprised of neurofilaments, structural proteins which allow for growth, with large, myelinated axons having the highest content.289–291 and reflects neurodegeneration in PD.291–294 Although NfL levels were not elevated in a meta-analysis considering all patients with PD290 and in one study exploring EV NFL levels,295 levels seem to be higher in more advanced PD296 and the more severe postural instability and gait disorders (PIGD)-subtype.298 Consistent inverse associations with cognitive scores have been reported,299–302 while NfL levels also predict more severe motor progression,285 cognitive decline303 and progression to milestones . Blood NfL may, therefore, be useful for trial stratification, although its potential use as a surrogate end point might depend on the disease stage of recruited participants and trial duration.304Blood NfL strongly correlates with CSF NfL42 in CSF, discriminating PD from PSP with good accuracy 305 as well as the use of a stepwise approach of firstly distinguishing synucleinopathies from non-synucleinopathies with skin α-syn SAA and then further distinguishing MSA from PD with NfL306 or by combining CSF NfL, CSF α-syn SAA and brainstem imaging.307 Similarly, PD progression is better predicted when combining markers with serum NfL, genetic status (ApoE4 and GBA) and validated prognostic clinical variables  predicting unfavourable progression better than individual markers.296The highest yield when using NfL seems to lie in combining it with clinical and disease-specific fluid biomarkers. Examples of this include the ratio of NfL to AβA range of imaging modalities have been explored for their biomarker potential . These iBox 2Transcranial sonographyultrasound echogenicity measurement of brain tissues or structures through intact cranium—limited by lack of bone window in some subjects and inter-technician variabilityStructural MRIquantification of brain structural change using regions-of-interest or whole-brain approaches1, T2, T2*, R2* (R2* = 1/T2*)-weighted, susceptibility-weighted, proton-density-weighted, fluid-attenuated inversion recovery and neuromelanin-sensitive approachescommonly used sequences include TProton magnetic resonance spectroscopyestimates relative concentrations of proton-containing metabolites in brainN-acetylaspartate, choline-containing compounds, myo-inositol and creatinemetabolites commonly assessed include Functional MRIevaluates neuronal activity by measuring transient variations in blood flow and variation correlation in functionally connected regionsutilized under task-based or under resting-state conditionsRadiotracer imagingmeasures pre- and postsynaptic receptor and transporter density as well as glucose metabolism and microglial activation using different radiotracersprovides information on nigrostriatal dopaminergic, serotonergic and cholinergic system integrity, regional tissue glucose metabolism and activity and status of microglial-mediated inflammation12 The range of imaging approaches that could be used for this are variable in their ability to discriminate PD from other pathophysiological processes as well as their potential for measuring the rate of progression of PD.In the proposed staging system for PD, the development of dopaminergic dysfunction has been incorporated as an important staging threshold.308–310 although a proportion of healthy controls and essential tremor patients also exhibit this.311 This sign can, however, differentiate PD from PSP and MSA with good sensitivity (91%) and specificity (82–96%).308 Hyper-echogenicity remains unchanged over follow-up312 and does not correlate with disease severity313 or presynaptic DAT loss,314 thus limiting use as a progression marker.Increased substantia nigra (SN) echogenicity, likely due to accumulation of nigral iron, is observed in PD,1-weighted structural imaging methods, which measure cortical and subcortical volumetric changes and brain atrophy; neuromelanin-sensitive T1-weighted imaging, which is sensitive to measuring neuromelanin-iron complexes; iron-sensitive MRI which captures iron deposition and dopaminergic cell loss; and diffusion imaging using either single-tensor or two-compartment diffusion modelling (free-water), which reflects neurodegeneration and/or neuroinflammation.Structural MRI approaches comprise; T1-based structural MRI methods comprise cortical thickness measurement, voxel-based morphometry (VBM) and deformation-based morphometry (DBM). Differences in these approaches are summarized in T315 This distinction is, however, best made in later disease stages at a time when disease modification approaches may be hardest to achieve. Novel automated indexes may improve this though will need to be tested in independent cohorts.316Structural differences in the midbrain, putamen, brainstem and cerebellum can distinguish PD from atypical parkinsonian disorders.317 A faster decline in prefrontal and cingulate cortices and the caudate and thalamus has also been seen in de novo PD compared with controls,318 while greater frontal atrophy after 18 months has also been noted in PD patients without cognitive impairment with a disease duration of only 2 years319 (though these findings were separately contradicted320).In the PPMI cohort, deformation-based morphometry detected a unique atrophy pattern, which predicted motor progression in early PD without dementia.321 while another found reduced grey matter in the frontal lobe.322 Longitudinal atrophy of occipital and fusiform regions has been noted in patients with a disease duration of over 5 years without cognitive impairment, while patients with cognitive impairment develop greater and more widespread atrophy in supplementary motor area, temporal, parietal and occipital cortices.323 Accelerated loss of gyrification in bilateral frontal and parietal regions in patients with a disease duration greater than 5 years compared to less than 5 years has also been noted.324Studies in individuals with moderate to late-stage PD without dementia have also varied. No VBM differences were noted in one study,1-weighted structural MRI methods are sensitive to neurodegenerative progression even in the absence of cognitive impairment, although this also seems to be better in more advanced disease stages. Replication studies demonstrating patterns of atrophy progression depending on disease stages are however currently lacking and will be important before recommendation for trial use. Furthermore, ascertaining the precise role of ultra-high-field scanners (7 T and above), which can provide sub millimetric anatomical information and higher degrees of diagnostic detail compared with 3 T MRI,325 will be important. Planned future longitudinal studies will be critical for informing this.326In summary, T327–331 while signal differences are also suboptimal for distinguishing atypical parkinsonian conditions from PD.333 In contrast, however, NMI shows reduced signal across disease stages (disease duration of 1.5–10 years) with a ventrolateral to anteromedial SN progression pattern consistent with the neuropathological patterns of cell loss.Neuromelanin imaging (NMI) demonstrates only moderate sensitivity and specificity for distinguishing PD from healthy controls,334–336 The absence of dorsal nigral hyperintensity corresponding to the region of nigrosome-1 (DNH) on iron-sensitive sequences distinguishes PD from controls well338 regardless of disease duration.339 Use for distinguishing atypical disorders from PD is however lacking, while progression marker use seems to be disease duration-dependent.Iron-sensitive techniques including R2* relaxation imaging, susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) have similar ability to quantify nigral iron deposition as NMI.340 separate studies exploring R2* or QSM in de novo patients336 and patients with a disease duration <1 year showed no longitudinal changes.339 The use of R2* as a progression marker becomes clearer, however, in later disease stages,339 with increased relaxation time in SN R2* mapping over 3 years correlating with motor severity in cases with an initial disease duration of 5 years,341 while faster progression in the SN pars compacta seems to occur after a disease duration >5 years.339Although striatal, nigral, globus pallidus and caudate R2* relaxation rate increased in two separate studies after 2 years in early-stage PD,Taken together, NMI and iron-sensitive imaging could potentially be developed usefully as progression biomarkers, although values will need to be considered in the context of disease duration. Obviously, the use of iron-sensitive modalities will be particularly advantageous in trials targeting iron.342–344 this was not confirmed by a meta-analysis of 10 studies.345 Evidence in later disease (disease duration 10 years) is limited to one study demonstrating more anterior and rostral SN involvement.344 On balance, this approach cannot currently be recommended for progression marker use. The finding of diffusion abnormality of the nucleus basalis of Meynert predicting development of cognitive impairment could be explored for balancing arms in small trials or selecting phenotypes that are likely to respond to specific treatments though replication of this finding is important.346Although some studies have demonstrated reduced SN fractional anisotropy with single tensor diffusion imaging in early PD,348 Free water in the posterior SN also increases over 4 years and changes over 1 year can predict the H&Y 4-year change.348 This increase continues in later disease stages (duration over 7 years), where longitudinal increases in free water occur in the anterior but not posterior SN.349 This modality is promising as a progression biomarker but may require selection of the region of interest depending on the disease stage. Free water imaging of the basal ganglia, midbrain and cerebellum and the application of automated imaging differentiation is promising for differentiating PD from atypical conditions.350 This approach was found to be superior to a conventional magnetic resonance Parkinsonism index as well as plasma NfL levels for distinguishing PD from atypical conditions.351Free water imaging studies have been more consistent with increased signal in the posterior SN being noted in early PD.N-acetyl aspartate/creatine (NAA/Cr) ratios in the SN are reduced compared to controls and correlate with disease severity.353 Lower ratios have also been noted in the lentiform nucleus (LN), temporoparietal and posterior cingulate cortices, as well as the presupplementary motor area,354–357 although correlation with disease severity is less clear.356 NAA/Cr ratios are lower in the rostral SN in PD with an inverted pattern in atypical parkinsonian patients and healthy controls.358 Taken together, there is some preliminary level of evidence that MRS could serve to improve PD diagnostics, but it may be best used in combination with conventional MRI to increase specificity.Proton magnetic resonance spectroscopy (MRS) reveals the metabolic status of the region sampled for a specific disease process. In PD, 31P-MRS) has been of specific interest for a subset of potential interventions as it can assess mitochondrial function. In vivo Pi/ATP and PCr/ATP ratios reflect oxidative phosphorylation pathways.359 Reductions in ATP and PCr360 and increased Pi/ATP ratios361 in the putamen and midbrain of PD patients compared with controls have been reported while differences can also distinguish PD from PSP (AUC 0.93).362 Longitudinal ratio improvement suggestive of target engagement was also noted in a recently completed disease modifying trial of ursodeoxycholic acid.363Phosphorus based MRS ,365 while cerebellar connectivity with multiple brain networks differs between PD and MSA.366 Longitudinal task-based functional MRI can track progression with declining activity in the putamen and primary motor cortex over 1 year,367 although the impact of levodopa administration on network connectivity is an important consideration.368 While the available evidence for this modality is promising overall, more widespread replication of diagnostic and progression findings are necessary.Resting-state and task-based functional MRI reveal networks involved in motor, cognitive and affective processes. Network impairments have been associated with motor and non-motor symptoms. Reduced resting-state connectivity between the striatum and thalamus, midbrain, pons and cerebellum has been noted in PD as have connectivity changes between cortical and subcortical areas.370 More recently, however, a newly developed α-syn PET tracer, 18F-ACI-12589, was shown to bind to basal ganglia and cerebellar white matter in a small cohort, although this was confined to MSA patients.371 Larger studies examining diagnostic accuracy for distinguishing PD from MSA will be critical.Several radiolabelled probes for imaging α-syn have been explored though no tracer is currently of diagnostic value for PD. Issues to overcome include developing tracers for intracellular targeting with ideal lipophilicity and tracer selectivity for α-syn over amyloid and tau aggregates.11C-dihydrotetrabenazine) and the DAT (DAT/tracers CFT PET and 123I-CIT SPECT) density.A variety of radionuclide tracers are available to examine pre- and post-synaptic striatal dopaminergic function using PET or SPECT imaging. At the presynaptic level, molecular targets and their respective tracers include L-aromatic amino acid decarboxylase [AADC/tracer fluorodopa (F-DOPA)], vesicular monoamine transporter 2  due to e.g. drug induced parkinsonism.373–375 Objective measurement of striatal uptake in comparison to other regions may, however, be more useful in trials recruiting patients with more established PD as these ratios can reflect motor and non-motor disease severity as well as progression through disease stages, although hemispheric dominance and type of tracer used are important considerations.376 Striatal dopaminergic markers decline most prominently in the first years of motor disease before largely plateauing within 5 years of diagnosis.377–380 Quantification of dopaminergic markers in the midbrain/SN may be better markers beyond this point.381These markers are sensitive for the detection of dysfunction or loss of striatal dopaminergic terminals and enable the identification of parkinsonian syndromes with nigral neurodegeneration but do not reliably distinguish PD from atypical disorders. Visual assessment for the presence of nigrostriatal degeneration with this modality is increasingly used in trial recruitment382 Quantitative dopaminergic assessments have been used in a number of recent disease modification trials though with overall negative findings to date  or agents such as 11C-NNC 112, which binds to D(1) receptors.383 Preservation of post-synaptic dopamine receptors is typical of PD whereas post-synaptic receptor loss early in the disease is more likely indicative of an atypical form of parkinsonism. Imaging results depend on the dose and timing of oral dopaminergic replacement and the usefulness of this type of imaging approach may perhaps be restricted to restorative approaches such as cell or gene therapy interventions.384Dopamine receptor expression can also be estimated at the post-synaptic level with PET ligands such as 385 Serotonergic denervation also correlates with increased dopamine turnover and reduced levodopa responses.386 In later disease stages (disease duration 5–10 or more years), serotonergic transporter binding remains reduced compared to controls,385 and the degree of serotonergic pathology is associated with cognitive decline.387 Cholinergic denervation also occurs in early PD (disease duration less than 3 years) but is more pronounced in PD with dementia.388 Noradrenergic activity, quantifiable by PET imaging is reduced in PD and is associated with the presence of RBD and cognitive impairment.389 The utility of these markers in tracking progression is of interest but not yet sufficiently clear.Radionuclide imaging studies of the serotonergic and cholinergic systems demonstrate associations with non-motor PD pathophysiology. Reduced binding on serotonergic imaging has been noted in individuals with early PD (disease duration less than 5 years).18F-UCB-H or 11C-UCB-J) reflect this and have been studied in several cohorts. Lower binding potential in both cortical and subcortical regions have been noted in PD though this is most prominent in the SN.390 Correlation with clinical status has, however, been inconsistent though one study suggested more prominent and extensive reductions in PD dementia and DLB cases.391–393 Similarly, small cohort studies using 11C-UCB-J PET did not note binding changes over 2 years.394 Current evidence therefore does not support the use of this marker in clinical trials.Synaptic density quantification irrespective of neurotransmitter type has also been of interest in PD. Tracers quantifying the concentration of the synaptic vesicle 2A protein  characterized by elevated pallidothalamic and pontine metabolic activity with reduction in the supplementary motor area, premotor cortex and parietal association areas has also been noted in cases prior to dopaminergic treatment398 and can differentiate PD from atypical parkinsonism.399400 although a critical limitation is that acute dopaminergic treatment diminishes the pattern.401 A PD-related cognitive pattern (PDCP) characterized by a reduction in the medial frontal and parietal association regions and metabolic increase in cerebellar cortex and dentate nuclei402 has also been described. This pattern seems to occur years after the PDRP,403 increases over time400 and is higher in those with dementia.404 The PDCP also correlates with memory and executive performance,402 while its lack of change with dopaminergic treatment potentially supports its use as a marker of cognitive dysfunction.405 These separate metabolic networks could potentially be used to track progression and treatment response in the appropriate setting.PDRP progresses in early PD (disease duration less than 2 years) over 24 months, suggesting potential progression marker use in the early stages,11C-PK11195, 11C-PBR28 and 18F-FEPPA, which bind to the 18 kDa translocator protein (TSPO) on mitochondria in microglia, have been used for imaging neuroinflammation with TSPO upregulation suggesting microglial activation.406The PET ligands 11C-PK11195 binding.407 Binding affinity can vary with TPSO genetic polymorphisms which needs appropriate adjustment in analyses.408 Taken alone, TPSO patterns lack the ability to distinguish parkinsonian conditions though their future use may be as biomarkers of therapeutic response for interventions targeting neuroinflammation.409PD clinical severity and putaminal presynaptic dopaminergic integrity correlates with A framework for considering the definition of PD according to the presence/absence of α-syn SAA-CSF is potentially a major step forward in planning PD trials. Several practical obstacles need to be considered however prior to the routine use/reliance on biomarkers in the clinical trial context. Firstly, acquiring some biomarkers, e.g. CSF, requires an invasive procedure, which may be unacceptable for some participants. Growing evidence of the equivalence of α-syn SAA-in skin to that seen with CSF could, however, overcome this limitation. The demonstration of equivalence of testing on even less invasive samples such as serum/plasma or within peripherally obtained EVs is therefore a priority. With greater demonstration of validity, routine testing of peripherally acquired biomarkers can become normal practice, for example the widespread availability of plasma NfL testing in healthcare laboratories.Interpretation of discrepant results between studies attributable to preanalytical and analytical confounders, different techniques employed and a lack of factoring of different protein species measured  needs careful critique. Similarly, imaging studies are affected by methodological discrepancies, including different assumptions for correction of serial data as well as sample size, power and study design caveats and the use of different outcome measures. Collaborative studies allowing analysis of larger sample sizes with adequate follow-up that employ standardized sampling and analysis methodology will improve these limitations, as demonstrated by the harmonization of large numbers of samples processed in the PPMI.The major limitation in biomarker discovery is undoubtedly difficulty with validation. Association between a change in a biological assay alongside a clinical state need not equal causation. For example, biological changes may represent healthy compensatory responses to a pathological process. Furthermore, even biomarkers that do reflect active processes of neurodegeneration may not have linear relationships over the course of disease particularly if production ultimately declines because of widespread tissue death. While it is possible to use clinico-pathological data for validation, confirmation that a biomarker predicts slowing of disease progression necessarily requires the identification of an agent which achieves this according to our threshold, whether that be clinical, patient reported, functional impairment or quality of life milestones, which have inherent limitations.2* sequences and plasma ferritin and prolactin levels were used as combined markers of target engagement and specific measures of treatment effect while structural imaging for measurement of brain atrophy and DAT-SPECT imaging was used to explore the impact of the agent on overall disease progression . Although clinical worsening in the deferiprone treated group complicates interpretation of how well the panel of biomarkers performed, one could argue that they did reflect the effect of the drug with decreased nigrostriatal iron content and plasma ferritin and increased plasma prolactin in the deferiprone group, while no inverse correlation between brain-structure volumes and iron content was noted in keeping with the negative clinical findings over a relatively short duration of follow-up.To date, no single biomarker can yet be recommended to act as a surrogate for clinical disease progression in PD. Combinations of fluid biomarkers invariably increase the strength of their individual predictive properties. While fluid and imaging biomarkers are often collected from the same trial participants, explorations of the utility of multiple fluid biomarkers as a panel alongside imaging in combination are rare. This approach was partly adopted in the recent deferiprone trial  where brChallenges for future trials will be in the choice of selection of suitable combinations of fluid and imaging biomarkers that complement each other. This will certainly need to be strongly guided by the biological action of the agent being tested and the stage of the disease of their participants being treated, although those biomarkers that appear to align most closely with disease progression should be prioritized. How much weight each biomarker in the panel will ultimately carry will become more easily evident following a positive clinical trial.410 Alongside trials in prodromal cohorts, there will remain a need to identify whether any disease modifying intervention has an impact on the 6–10 million people already struggling with symptoms and in need of prevention of further decline.The identification of a better framework for the certainty of a PD diagnosis based on positivity of α-syn SAA-CSF is a major step forward, and less invasive equivalent alternatives will help even more. The further development of reliable biomarkers of PD neurodegeneration could further facilitate prognostication, identification of disease subtypes, conduct of clinical trials and identification of agents that may slow down or stop these processes. The precise role for biomarkers will depend on the mechanism of action of the agent in question, and the decision made regarding the stage of the illness at which the intervention is being applied. There is interest in recruiting people earlier in the neurodegenerative process, even prior to symptom onset, given that, intuitively, earlier intervention may provide a better chance of preventing irreversible cell death.In this group, PD diagnosis is less difficult though a sizeable proportion of cases at this stage with atypical parkinsonian disorders can be mistaken as suffering from PD and therefore inadvertently recruited into disease modifying trials. While there will remain healthy debate whether α-syn oligomeric seeding and propagation is the primary cause of PD neurodegeneration, it appears that the α-syn SAA-CSF assay reflects an α-syn-related neurodegenerative process and can reliably distinguish synucleinopathies from other causes of parkinsonism/tremor with high specificity.411 Mutations in GBA1 confer a worse prognosis and therefore a trial enriched with these patients may potentially allow an earlier signal of efficacy. In parallel, enhancement of GCase activity may also have therapeutic benefits in PD patients without GBA1 mutations.412PD subtyping is also a high priority for better selection of responders. For example, interventions that specifically target an aspect of disease pathophysiology associated with genetic abnormalities could be specifically tailored to these patients.180 and reflect different aspects of disease-related pathways would be a useful approach to stratify patients into prognostic groups and potential responders to the treatment being tested, which will in turn enable more efficient and cost-effective collection of data and increase the likelihood of detecting an effect.Features that strongly predict subsequent disease progression need to be carefully considered during treatment allocation. The randomization process itself should lead to balancing of features between placebo and active treatment arms, however this can fail to achieve this in smaller sized trials. The application of a panel of biomarkers for example pro-inflammatory immune markers which predict faster progressionThe most useful function of biomarkers is in the prediction that a change in any such biomarker reliably predicts slowing down of the neurodegenerative process that translates to reduction in disability accrual, and maintenance of function and quality of life. Towards this, the ratio of phosphorylated or oligomeric α-syn to total α-syn in CSF appears to be an encouraging fluid biomarker for disease progression. Technical challenges notwithstanding, measurement of one or both of these ratios may become routine practice in clinical trials of disease modifying agents to further improve diagnostic precision at baseline, minimize difference between trial arms and monitor changes in response to the intervention. The selection of a single fluid biomarker is likely to be a lower sensitivity surrogate for disease progression than the use of a panel of biomarkers. The development of a poly-biomarker, analogous to a polygenic risk score, will require careful modelling in large cohorts that have collected identical panels using agreed standardized operating procedures for their collection.There are several structural imaging techniques that seem to track disease progression in PD reliably, perhaps the most useful of which are neuromelanin or free water MRI. Whether these allow sufficient resolution to quantify changes over shorter time periods than needed for conventional clinical methods, requires further data. Functional or PET imaging may allow more rapid confirmation of target engagement in trials, and their routine use may depend on the putative mechanism of action of the intervention, e.g. TSPO PET, in a trial of a neuroinflammatory intervention. While stabilization of fluid, imaging or tissue biomarkers should mirror attenuation of α-syn aggregation within the brain, it remains to be seen whether change in biomarker activity can reliably predict subsequent clinical disease progression.In terms of recommendations, during the design and conduct of a clinical trial of a disease modifying intervention in PD, we suggest:For broad interventions, investigators should routinely collect a biomarker  that can be used for an α-syn SAA as part of the trial inclusion criteria. Currently, SAA offers the highest specificity in distinguishing PD from controls or PD-like conditions, but it’s utility in differentiating PD from MSA requires further assay refinement.For precision interventions, investigators should consider whether the planned intervention targets an alternative process that can be defined by an alternative genetic marker  or measurable pathophysiological process , irrespective of α-syn SAA.Investigators should consider incorporating such a biomarker within the trial inclusion criteria, while also ensuring the biomarker is appropriate for the stage of disease being studied.Where appropriate, the same biomarker might also be used to confirm target engagement of the intervention.Clinical outcome analyses may need to incorporate baseline differences in panels of wet biomarkers as well as imaging differences between treatment groups predictive of more rapid progression.Investigators should formally evaluate the relationship between biomarker changes and predicting the clinical effect of the intervention.Consideration should be given at an early stage how biomarker data can be usefully shared/integrated to maximize learning across interventions.413 Differences in the longitudinal change in biomarkers according to candidate interventions will undoubtedly help in the understanding of target engagement and help in the eventual prediction of long-term outcomes and ultimately are likely to become reliable surrogate outcome measures.Until we have identified an agent that slows down clinical progression, it will be difficult to conclude the validity of any biomarker at predicting such disease modification. It appears as a somewhat circular argument therefore, that we need success, before we can be confident in our tools designed to help achieve success. Faced with this challenge, the most practical path forward is to systematically collect specimens from participants in clinical trials for future research, while also incorporating longitudinal measurement of encouraging biomarkers for continued comparison with clinical progression measures. This requires a degree of consensus in the PD trials community regarding standardized protocols for specimen collection and analysis. The Critical Path for Parkinson’s (CPP) consortium is helping to achieve this.414 This decision has been controversial, and it is likely that a more robust conclusion in PD would only be reached once any combination of biomarkers has been comprehensively validated in relation to patient reports of clinical symptoms of relevance to their health and wellbeing. In the meantime, the best biomarker candidates can already likely improve the selection of participants and may contribute to early assessments of target engagement and of efficacy in counteracting pathophysiological mechanisms. An ongoing systematic process of confirming clinico-biomarker validity and utility is required.In conclusion, we should remain optimistic that the use of a combination of fluid, tissue and imaging biomarkers may become sufficient to reliably demonstrate disease modification. There is already a precedent that change in an imaging biomarker has been considered sufficient evidence, by some, to conclude disease modifying properties of aducanumab in AD.awad265_Supplementary_DataClick here for additional data file.


Nature Communications reveals that Mycobacterium tuberculosis can hijack epigenetic machinery in host cells and induce host cell ferroptosis, which promotes pathogen pathogenicity and spread. These findings also suggest new therapeutic strategies to treat tuberculosis.A recent study from  Mycobacterium tuberculosis (Mtb) bacteria in the lung and other organs, results in more than one million deaths every year and remains a significant global health threat1. The development of more effective therapies to eliminate this infectious disease requires a deeper understanding of interactions between Mtb and host cells2. Mtb infection can cause necrotic death of host cells, facilitating the release and subsequent dissemination of Mtb to other cells. Therefore, deciphering the nature of the necrotic cell death induced by Mtb is crucial for designing novel host-directed therapies to limit Mtb dissemination.Tuberculosis, an infectious disease caused by infection with 4. Harmful lipid peroxides are generated by cellular metabolic activities, but under normal conditions are kept in check by various anti-oxidant defense systems. Chief among these cellular systems is glutathione peroxidase 4 (GPX4), which uses glutathione as a co-factor to detoxify lipid peroxides and maintain cell survival5. Disabling this major ferroptosis defense system by suppressing GPX4 expression or activity leads to unchecked lipid peroxidation, cell membrane rupture, and ferroptotic cell death5. Dysregulation of ferroptosis has been implicated in a variety of diseases and pathological conditions, including cancer, neurodegenerative diseases, and ischemia/reperfusion-induced organ injury7. Interestingly, a recent study showed that Mtb infection reduced GPX4 expression and increased lipid peroxidation in host cells, and Mtb infection-induced necrotic cell death in culture and pulmonary pathology in vivo were alleviated by treatment with ferroptosis inhibitors, findings that causally link ferroptosis to Mtb-induced cell death and tissue necrosis8. However, the molecular mechanisms underlying this regulation have remained unclear.One type of necrotic cell death studied extensively in recent years is ferroptosis, which is triggered by excessive lipid peroxidation on cellular membranesNature Communications9, Qiang et al. set out to tackle this question by exploring the potential involvement of Mtb-encoding kinases and phosphatases in modulating host cell ferroptosis, considering the known effects of these proteins on diverse cellular processes in host cells. These analyses identified protein tyrosine phosphatase A (PtpA) as a pro-ferroptosis factor. Further experiments revealed that Mtb with ptpA deletion (Mtb ΔptpA) was less able to decrease GPX4 expression and induce ferroptosis in host cells than wild-type Mtb, and that restoring GPX4 expression in wild-type Mtb-infected host cells partially suppressed Mtb-induced ferroptosis. These data are in line with previous findings8 and further establish PtpA as a key Mtb effector for suppressing GPX4 expression and promoting host cell ferroptosis.In a new study in 10. RNA sequencing analyses showed that Mtb infection suppressed GPX4 expression at the mRNA level, prompting the authors to hypothesize that PtpA might suppress GPX4 transcription in the nucleus. A series of elegant experiments performed by the authors support this hypothesis. First, Qiang et al. showed that PtpA translocated into the nucleus by interacting with GDP-bound Ran GTPase , but this interaction was independent of PtpA’s phosphatase activity; importantly, a PtpA mutant that cannot interact with Ran-GDP also lost its ability to induce ferroptosis in host cells.PtpA is an Mtb secretory effector protein that not only functions as a phosphatase in the cytosol but is also capable of regulating transcription in the nucleus11. Consistent with this, PRMT6 was shown to suppress GPX4 expression in a methyltransferase-dependent manner. Notably, the ability of PtpA to regulate GPX4 expression or ferroptosis was lost in cells deficient in PRMT6 or cells treated with a PRMT6 inhibitor, demonstrating that PRMT6 is required for Mtb PtpA-induced ferroptosis. Additional experiments suggested that Mtb PtpA interacted with PRMT6 and promoted PRMT6’s methyltransferase activity to add H3R2me2a marks on the GPX4 promoter, resulting in suppression of GPX4 transcription and induction of ferroptosis. Importantly, this interaction seems to be critical for Mtb pathogenicity and dissemination in vivo: animal experiments with Mtb infection showed that Mtb harboring a PtpA mutant incapable of interacting with PRMT6, as well as Mtb ΔptpA, was less able to cause pathogenicity and dissemination in the mouse lung than wild-type Mtb.In addition, a yeast-two hybrid screening identified protein arginine methyltransferase 6 (PRMT6) as a PtpA-interacting protein. PRMT6 catalyzes the asymmetric dimethylation of histone H3 at arginine 2 (H3R2me2a) and suppresses gene expression9. According to their model  for ferroptosis suppression;6 therefore, the effect of vitamin E or selenium supplementation on treating tuberculosis can be explained, at least in part, by their roles in suppressing ferroptosis. These new findings9 suggest that ferroptosis inhibitors or drugs that specifically disrupt the interactions of Mtb PtpA with Ran-GDP or PRMT6 can be explored for tuberculosis treatment. More broadly, these findings12 together highlight the possibility of using ferroptosis inhibitors to treat diverse infectious diseases.On the translational level, previous studies have already shown the effectiveness of vitamin E or selenium supplementation in treating patients with tuberculosis


Postoperative PBI leads to unnecessary large irradiated breast volumes due to artifacts, including seroma.2 Five studies reported results on single-dose external beam preoperative PBI ranging between 15 and 21 Gy.2 Treatment with this relatively high dose led to mainly mild toxicity and good to excellent cosmetic outcomes in the majority of the patients. A remarkable result is the increased rate of pathologic complete response (pCR) after a longer interval of 6–8 months (42%) in comparison with a shorter interval of 2–8 weeks between radiotherapy and surgery (0–15%).2 Therefore, extending the interval could lead to an even higher response rate.Recent studies have reported good to excellent clinical and oncological outcomes in patients treated with preoperative PBI followed by BCS.3 This could reduce the treatment burden, facilitate healthcare logistics, and reduce healthcare costs. The positive predictive value of magnetic resonance imaging (MRI) alone is 67%, which is not sufficient to predict a pCR.4 Combining MRI parameters with biomarkers, such as gene expression profiling, specific immune profiles, and circulating tumor DNA could result in more accurate prediction of pCR after preoperative single-dose PBI in low-risk breast cancer patients.5The ultimate goal is to omit surgery in future low-risk patients with a pCR. For this purpose, it is necessary to be able to predict a pCR accurately after single-dose PBI. Even when patients do not reach a pCR after preoperative PBI, the advantage of this approach is single-dose radiotherapy instead of the standard multi-fractionated radiotherapy .