Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health. The prevalence of CVD risk factors including hypertension, type 2 diabetes (T2DM), and lipid levels have increased rapidly over the last two decades. Atherosclerotic CVD (ASCVD) phenotypes are heterogeneous. The presence of subclinical ASCVD precursors like vascular dysfunction can be measured as endothelial dysfunction, arterial stiffness, or microvascular dysfunction. Subclinical structural changes can be detected by carotid intima-media thickening (CIMT), plaque deposition, coronary artery calcium (CAC), and reduced ankle-brachial index (ABI), all of which can predict future ASCVD events. ASCVD affects South Asians earlier in life, with 52% of CVD deaths in individuals <70 years compared to 23% in the West, disparities that are not fully explained by differences in conventional risk factor burden.Cardiovascular disease (CVD) remains the most important cause of mortality worldwide. CVD is now the leading cause of mortality in India, accounting for 25% of deaths. The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner BMI than for Whites.Heart failure (HF) is a complex clinical syndrome that results from structural and functional impairment of ventricular filling or output, and manifests itself in heterogeneous structural phenotypes (HF with preserved [HFpEF] or reduced ejection fraction [HFrEF]). HF prevalence in the US is projected to increase 46% from 2012 to 2030, resulting in over 8 million adults (≥18 years) with HF. Although numerous risk factors for HFpEF have been identified including hypertension, older age, female sex, obesity, diabetes, and renal disease, there are currently no class I guideline recommended treatments for HFpEF that improve mortality. HFpEF has received increased attention since HFpEF patients frequently experience delayed diagnosis and have limited treatment options. Recent studies have shown that HFpEF is a clinically heterogeneous disorder, consisting of subgroups with related comorbidities and pathophysiologies, which lead to different progression trajectories. Employing latent class analytics and clustering techniques based on widely available clinical variables, several investigators have shown that patients with HFpEF can be divided into distinct classes with differing outcomes.Nearly half of the HF patients have HFpEF, with >90% being >60 years old, with rapidly increasing numbersCVD progression can be affected by both gene and environment via different molecular pathways and mechanisms. Although the high throughput technologies have enabled accurate and cost-effective genotyping in large population samples, comparable high throughput measurements of environmental exposures are needed for large population studies. Gene-environment interaction is a common mechanism to explain complex disease risk, and inter-individual variability. Better understanding of gene-environment interactions and their causal relationships will point to pathways and mechanisms as potential targets for treatment and intervention. The gene-environment interaction study may also help understand the CVD risk among immigrant populations exposure to different environmental and lifestyle factors.In this paper, we focus on the current progress of omics studies on ASCVD and HF, as well as the anticipation of implications among South Asian population. A summary of selected CVD omics studies listed are shown in, ASCVD, HF, and their risk factors, such as BMI, blood lipids, blood pressure, and T2DM; however, these genetic variations explain only a small portion of risk in populations. Joint genetic-environmental effects may be a key mechanism responsible for unexplained CVD risk. For example, environmental exposures can modify the gene expression levels through epigenetic mechanisms and this epigenetic modification can be inherited across cell generations to exert a long-term impact on the development of CVD.Genome-wide association studies (GWAS) have identified a large number of genetic loci associated with coronary heart disease. Earlier studies of PRS showed that the European ancestry-based can be transferred in other ancestry groups including South Asians, the associations of European ancestry-derived PRS were typically weaker in non-European ancestries. With large GWAS results from multiple ancestry groups, the PRS can be optimized to present ancestry-specific genetic risk for CVD. A study of 7,244 South Asian UK Biobank participants derived a PRS of CAD for South Asians from the previous GWAS findings that are primarily European-based. The PRS included 6,630,150 common variants, and demonstrated a successful framework for developing ancestry-specific PRS. In another study, researchers identified significant association between the GRS, which comprised of 29 genome-wide significant blood pressure variants found among European descent, and blood pressure among South Asians.A large number of genetic associations have been identified in large population studies for CVD and risk factors. Although identified genetic associations have small effect sizes individually, polygenetic risk score (PRS) can combine such individual effects into a much stronger predicter of a disease trait. A few studies have shown the successful identifications of CAD and relevant traits. Recent studies start showing the benefits of including diverse ancestries in discovering novel genetic loci associated with diseases, and improving the variance explained across ethnic groups. The South Asian population, who constitute over 20% of humanity, remain underrepresented in large genomic, epigenomic and other -omic studies. More GWAS in South Asians would improve both ethnicity-specific, and trans-ethnic discoveries of ASCVD- and HF-related loci, thus, address the high burden of these diseases in this large and growing population.Current findings in CVD genetics are overwhelmingly driven by European ancestry, that disproportionally represents the majority of the global population at risk. Epigenetic modification, through DNA methylation (DNAm) and other molecular mechanisms can regulate gene expression levels that can influence susceptibility to disease development, including atherosclerosis and chronic inflammation, two important pathophysiological processes leading to CVD. Furthermore, epigenetic markers are modified by age and environmental risk factors, such as smoking and poor nutrition. Thus, the epigenetic profile can capture many of the cumulative environmental effects that influence susceptibility to CVD and its adverse outcomes. An epigenome-wide association study (EWAS) is a study of epigenetic markers across the entire genome in a population exhibiting a specific trait. EWAS provides an unbiased approach for identifying molecular mediators of genetic and environmental factors that may explain residual risk of disease and has been applied to investigate CVD and risk factors.Epigenetics refers to molecular modifications that are unrelated to the primary DNA sequence and that can arise from environmental exposures. This robust study reported epigenetic associations with effect sizes of a clinically relevant magnitude. Another EWAS identified 59 DNAm sites that associated with risk of dilated cardiomyopathy in left ventricular and peripheral blood samples. Bioinformatic analyses of differentially methylated regions showed enrichment for modification around binding sites for transcription factors involved in cardiac phenotypes. Studies in large populations have also identified DNAm sites associated with traditional CVD risk factors including age, BMI, diabetes, blood lipids, smoking and inflammation. These DNAm markers may provide a measure of longitudinal CVD risk, independently predicting future CVD events. However, DNAm sites need to be rigorously examined across genetically distinct cohorts. The study of incident T2DM conducted among Indian Asians and Europeans showed a 2.5 times higher adjusted risk among Indian Asians than Europeans, and five loci includingABCG1,PHOSPHO1,SOCS3,SREBF1, andTXNIP were associated with incident T2DM among Indian Asians and replicated among Europeans. The other study of incident T2DM reported additional loci such asPHGDH andCPT1A, which were discovered among Europeans and replicated among Indian Asians. The study of blood pressure compared the methylation profiles between Europeans and South Asians revealed many distinct loci between the two ancestries with a small overlap. To our current knowledge, some known trans-ethic epigenetic loci might be transportable from Europeans to South Asians, but there is still a lack in studies specifically among large South Asian populations to further explore novel loci to explain the higher risk. A number of EWAS have examined DNAm patterns associated with air pollution, which is a known environmental risk factor for CVD. Since epigenomic profile can be modified due to changes in environmental and socio-behavioral factors, a longitudinal study can reveal the dynamics of the epigenomic profile, and potential causal or mediation effects in relation of CVD risk and progression. In sum, epigenetic profiles provide a signature of the cumulative burden of life-long exposure to CVD risks.A recent EWAS of 11,461 individuals of European or African ancestry identified 52 DNAm sites significantly associated with incident coronary artery disease  using peripheral blood samples. A recent study of the healthy human heart tissue collected from autopsy determined the healthy heart proteome. The resulted database, which included over 10,700 proteins, is a comprehensive resource for the downstream investigations. In a targeted proteomics study, two protein signatures for high-risk plaques and absence of coronary atherosclerosis were identified among a cohort with suspected coronary artery disease. The prediction accuracy of a model constructed by 50 proteins showed a better prediction accuracy in adverse cardiovascular events than a traditional risk factor model. These findings are critical in CVD risk prediction and differentiation of CVD subtypes. In addition, gene expression profiling in CVD also enables a better understanding of pathophysiology of CVD. Patterns of gene expression of human aorta tissue was investigated to identify genes with prediction power in atherosclerosis. Studies of non-coding transcriptome, which even though have limited protein-coding functions, are discovering the pathology of CVD. To eventually realize precision medicine, we are still facing the challenges of standardization of methodologies and translation. In addition, researches in this area largely depend on the availability of tissues from autopsy, thus the clinical translation and implementation has been limited. However, such studies facilitate a better understanding on the disease causal pathway and mechanism. Particularly, there has been a lack of similar researches particularly among South Asians, which is urging the future efforts of investigation.The proteomics technologies have evolved rapidly in the past two decades. Recent applications of proteomics in population studies have produced interesting findings in CVD research. It reflects the combined systemic effects of genetic, lifestyle, and environmental factors. Metabolomics is an emerging discipline that has the potential to transform the study of biological responses to environment exposures that underlie disease development. The untargeted metabolomic approach provides unbiased coverage of metabolites with greater breadth than targeted methods. Advances in untargeted metabolomics have increased the number of metabolites analyzed, thereby improving accuracy of disease detection and quantification. Metabolomics holds promise in elucidating interactions between genes and environment (such as air pollution) to uncover the pathophysiology and underlying molecular pathways of complex disorders such as ASCVD and HF.The metabolome is a global identification of all small molecules produced by cells during metabolism or obtained from environmental exposures. The metabolome thus provides a direct functional readout of cellular activity and physiologic status that can potentially be used for early disease identification, study of treatment effects, and for prognostication of disease progression. Metabolomics study of dietary patterns among Asian Indians were found associated with cardiometabolic risk. A study of 145 Asian Indians in the Metabolic Syndrome and Atherosclerosis in South Asians Living in America (MASALA) pilot study revealed that the metabolite pattern of branched-chain amino acids, aromatic amino acids, and short-chain acylcarnitines, which are representative of a “Western/nonvegetarian” dietary pattern associated with adverse cardiometabolic profile. Recent studies also reported changes in global metabolism in relation to HF risk and outcomes. A study of 515 HF patients identified a panel of metabolites that improved prediction of HF-related mortality and re-hospitalization, with variation between HF subgroups. By demonstrating diagnostic and prognostic value in HF risk, these studies suggest that metabolomic research will distinguish HF subtypes.Metabolomic research in humans has shown that modification or dysregulation of numerous metabolites, including amino acids, phospholipids, short-chain acylcarnitines, and nitric oxide synthesis, are associated with CVD risk and outcomes. In a study of 2,232 African and 1,366 European Americans from the Atherosclerosis Risk in Communities (ARIC) study (633 incident CAD cases), 19 metabolites collectively improved CAD risk prediction. Recent GWAS have identified >160 genomic loci for CAD, 11 loci for HF, and >300 loci for T2DM. However, biological functions of most identified genetic loci remain unknown. Therefore, assessment of the functional linkage between identified epigenetic makers, metabolites, and genetic variants would be fruitful. Unlike the genome profile, epigenomic, transcriptomic, proteomic and metabolomic profiles can be modified by environmental exposures, physiological conditions and disease status. Genomic data will complement epigenomic and metabolomic markers by identifying complex biological processes at the systems levels. Current omics studies predominantly use a cross-sectional design, which enables the novel biomarker discovery but is limited to infer causal associations due to confounding and revers causation. A longitudinal design including baseline omics and incident CVD would better demonstrate the prediction utility of omics markers for CVD progression, and has been implemented in omic association studies in other ancestry groups. However, such a design doesn’t incorporate the longitudinal changes of omics markers in relation to varying environment, pathobiology and disease progression. Repeated measurements of omics profiles excluding genomics would be important to understand long-term risk and natural history of chronic diseases such as CVD. Such omics changes may also help identify reversible targets for novel interventions for CVD outcomes.Genetics is one of the primary sources of epigenetic and metabolic variation. Although increasing number of population studies have measured multi-omics data, recent studies have focused on single -omic association study and used additional -omics data to better understand the molecular functions of identified associations. Integrated multi-omics studies of CVD outcomes have been limited. A large HF study of over 8,000 participants within the Framingham Heart Study utilized integrative trans-omics data including genetic variations, DNA methylation, and gene expression data to reveal genetic contributions towards HF. The transportability of such findings to South Asians needs to be evaluated. Another study integrating DNA methylation and gene expression data identified independent latent factors associated with CVD. The unsupervised machine learning of multi-omics successfully improved classification and discrimination. Additionally, our recent joint epigenomics-metabolomics study of smoking demonstrated that these multi-omic layers capture complementary components of biological systems in response to widespread risk exposures such as air pollution. By jointly analyzing genomic, epigenomic, and metabolomic profiles, we hypothesize that it could lead to identification of key genes and pathways that may be the molecular mediators of CVD. The molecular functions of identified epigenetic and metabolic markers, key genes and pathways involved in subclinical and clinical CVD will help us develop future targeted studies to improve comorbid disease prevention and clinical care strategies.A recent study using longitudinal big data including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring have showed the potential of revealing cardiovascular pathophysiology on a molecular basis. Longitudinal design can also distinguish cause from consequence using appropriate modeling. With large sample size, properly implemented mediation analysis and strong genetic instrumental variables for Mendelian Randomization analysis, future longitudinal studies in South Asian populations can further control for genetic and environmental confounders to better address causal relationship between -omic markers, environmental factors and CVD.To extend this understanding to high-risk populations such as South Asians, it is important that such studies be performed in longitudinal cohorts that adequately represent the ethnicity and the environment. A longitudinal design enables the detection of changes in the characteristics of the target population at both the group and the individual level. Since the multi-omics profile  can be modified by dynamic and cumulative environmental factors, capturing the longitudinal multi-omics would benefit the understanding of risk development and progression of subclinical and clinical CVD in South Asians. Longitudinal changes of individual omic profile related to disease and aging have been documented in humans, primates and mice. For GWAS, tools such as PLINK, RVTESTS and GENESIS now allow the incorporation of many data pieces such as genotypes, annotations, allele frequencies and phenotypes to be processed efficiently in particular formats. For untargeted MWAS, mixOmics and xmsPANDA  has been utilized to conduct feature selection, and the software Mummichog for pathway exploration based on untargeted metabolomics data has been made available to bypass the feature identification stage. In addition, various tools have been developed for network analysis. For example, the weighted gene co-expression network analysis can be implemented using WGCNA to identify clustering of genes, the software xMWAS can perform the integration and differential network analysis for multiple layers of omics data. The evolving omics researches of cardiovascular risk are coupled with these tools to achieve better understating of the disease biological mechanism and pathway.Due to the rapidly growing technologies such as next generation sequencing and untargeted metabolomics, massive amount of accurate data can be obtained in a cost-effective manner. Therefore, there has been an urgent need for new methodologies and algorithms to form, for the purposes of computationally intensive data managing and analysis. T2DM is also a multi-factorial disease that involves numerous genetic pathways and many environmental factors, and has high prevalence in South Asian populations. Recent studies of T2MD subgroups have revealed striking heterogeneity of T2DM risk, etiology and outcomes, which may be further illustrated by multi-omic profiling. Lastly, multi-omics can help explain inter-individual variability in response to environmental risk exposures. Exposures to environmental risk such as air pollution (common and severer CVD risk in South Asia) are multifactorial and time-varying, thus, their measurements can be incomplete, costly, and imprecise for pathophysiological effects. Omic technologies such as epigenomics and metabolomics represent exogenous and endogenous effects related to CVD risk and have emerged as key components of exposome measures. They can capture the biological response to environmental exposures, thus, providing more precise risk assessment for subclinical and clinical CVD. Improved omics measurements of environmental exposure will also enable large scale gene-environment interaction study to further uncover molecular mechanisms underlying CVD pathophysiology.South Asians are an understudied population at high CVD risk even at low body weight and young ages, with a high propensity to diabetes, dyslipidemia, and hepatic steatosis, features that may provide new insights into CVD risk in the presence and absence of traditional risk factors. Given the genetic and molecular underpinning of CVD and risk factors, the genetic and molecular markers identified from multi-omics research may help accurately profile the CVD risk, given the unique characteristics among South Asians. Secondly, the multi-omics approach also holds the promise of revealing the heterogeneous mechanisms of CVD and risk factors. For example, HFpEF patients can be clustered into distinct subclasses with different clinical outcome using available demographic and clinical variablesIn addition to common genomic and multi-omics factors of CVD across ancestry groups, studying multi-omics among large population samples within South Asians may also discover genetic variants or molecular signatures unique for South Asians. Incorporating these multi-omic profiles can optimize the diagnosis, treatment and prognosis of CVD, which is the most important and still growing health burden for South Asian populations., which is a large longitudinal study of 28,000 subjects across three large cities in South Asia. Studies that employ the integrative multi-omic approach to disentangling complex molecular systems underlying CVD are still anticipated. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health. Combining high-resolution untargeted metabolomics, epigenomics with a rigorous, longitudinal design would provide comprehensive molecular characterization of subclinical and clinical CVD among South Asians – a large global population with unique CVD patterns, and with potential variations in phenotypes. To fully understand the gene-environment interplay, it would also be useful to have studies of South Asians living in South Asia as well as South Asian emigrants.Despite the available tools and fruitful research conducted among European ancestry, the implementation of similar research among South Asians remains challenging. Large high-quality studies are needed, with the requirements of high volume recruiting of population-based study samples, well-defined disease and phenotypes, long time follow-up, establishment of data registries, close collaborations between scientists with various expertise, such as study design, molecular biology and bioinformatics. There is a growing effort of research among the South Asian population, such as the Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) studyNo data are associated with this article. I believe the authors have adequately addressed my comments. Thank you.Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?PartlyReviewer Expertise:Statistical genetics and genomics.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. The authors have satisfactorily revised the article in response to reviewer comments.Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?PartlyIs the topic of the review discussed comprehensively in the context of the current literature?NoReviewer Expertise:Cardiovascular disease epidemiology, South Asian cardiovascular health and disease prevention.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. In the review article “Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?” by Sun et al., the authors provide a summary of research findings from genetic, epigenetic, and metabolomic studies of cardiovascular risk factors and cardiovascular disease. The narrative begins to detail how these “multi-omic” approaches may be used to better understand the mechanisms of cardiovascular diseases, and concludes with a recommendation to increase “multi-omics” research in the South Asian population, with particular emphasis on longitudinal epigenomics and metabolomics to comprehensively characterize subclinical and clinical cardiovascular disease at the molecular level. The authors have identified and described an important and growing field of research that is relevant to South Asians, a population that is disproportionately affected by cardiovascular diseases. A number of comments and suggests are submitted for the authors’ consideration to strengthen the relevance, clarity, and impact of their review:The narrative review of “multi-omics” provided by the authors is superficial, and does not sufficiently detail these growing methodologies. The authors are encouraged to broaden their narrative of these -omics tools, including recent findings and how these tools are being used to develop strategies to improve cardiovascular health in European ancestry populations (which the authors acknowledge are the populations for which most data are available). This broader narrative and contextualization would more comprehensively describe the current state of this field, and help the reader understand how -omics approaches may be applied in South Asians..) This and other recent similar studies would be helpful to include. For instance, recent GWAS have been conducted in South Asian diaspora populations, and have contributed to a variety of strategies to understand cardiovascular risk in this population such as polygenic risk scoring :703-14Since the narrative review is cursory, it is not clear how the authors envision “multi-omic” methodologies should be deployed in South Asian populations. What are the key research questions with these methods in the South Asian population? What do the authors hypothesize will be found? Are there any characteristics specific to the South Asian population that should be accounted for ? Addressing these questions seems important for this review to understand how longitudinal multi-omics might “shed light” on CVD in South Asians.Are longitudinal -omics a component of research in other (including European ancestry) populations? What insights have been gained from such work? The authors suggest a longitudinal -omics approach in their concluding paragraphs, but have inadequately supported the potential merits of this strategy.This review would be a prime opportunity to move this field forward beyond only stating that these -omics tools should be applied in South Asian populations. What are the existing challenges/barriers preventing these tools from being implemented in the study of South Asian CVD and CVD risk?  What strategies would help overcome these barriers? The authors are recommended to consider addressing these questions in their review to provide important context to the state of the science and a roadmap to achieve their recommended future directions.The authors’ concluding paragraph introduces new concepts that were not previously discussed . Consequently, their conclusions seem to be obscured and do not follow from their narrative. I recommended discussing these components of research gaps in South Asians earlier in the review, in order to justify their conclusions.  Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?PartlyIs the topic of the review discussed comprehensively in the context of the current literature?NoReviewer Expertise:Cardiovascular disease epidemiology, South Asian cardiovascular health and disease preventionI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. 1. The narrative review of “multi-omics” provided by the authors is superficial, and does not sufficiently detail these growing methodologies. The authors are encouraged to broaden their narrative of these -omics tools, including recent findings and how these tools are being used to develop strategies to improve cardiovascular health in European ancestry populations (which the authors acknowledge are the populations for which most data are available). This broader narrative and contextualization would more comprehensively describe the current state of this field, and help the reader understand how -omics approaches may be applied in South Asians.For instance, recent GWAS have been conducted in South Asian diaspora populations, and have contributed to a variety of strategies to understand cardiovascular risk in this population such as polygenic risk scoring :703-141.) This and other recent similar studies would be helpful to include.We appreciate the comments and suggestions. In response to reviewer 1’s comments, we included a summary (Table 1) of recent omics studies of CVD in European ancestry and multi-ethnic populations. We also summarized growing methodologies and analytical tools which could be used to improve cardiovascular health among South Asians. We have added the following paragraph of “Strategies of omics studies” in the revised manuscript paper as below: "Due to the rapidly growing technologies such as next generation sequencing and untargeted metabolomics, massive amount of accurate data can be obtained in a cost-effective manner. Therefore, there has been an urgent need for new methodologies and algorithms to form, for the purposes of computationally intensive data managing and analysis.[116] For GWAS, tools such as PLINK,[127] RVTESTS[128] and GENESIS[129] now allow the incorporation of many data pieces such as genotypes, annotations, allele frequencies and phenotypes to be processed efficiently in particular formats. For untargeted MWAS, mixOmics[130] and xmsPANDA  has been utilized to conduct feature selection, and the software Mummichog[131] for pathway exploration based on untargeted metabolomics data has been made available to bypass the feature identification stage. In addition, various tools have been developed for network analysis. For example, the weighted gene co-expression network analysis can be implemented using WGCNA[132] to identify clustering of genes, the software xMWAS[133] can perform the integration and differential network analysis for multiple layers of omics data. The evolving omics researches of cardiovascular risk are coupled with these tools to achieve better understating of the disease biological mechanism and pathway."We agree that the polygenic risk score study by Wang M et al is a great example showing how to use existing GWAS findings and data of CAD to optimize the utility in South Asians. We added the following discussion about polygenic risk score in the “Genetic basis of atherosclerotic cardiovascular disease and heart failure” section as below: "A large number of genetic associations have been identified in large population studies for CVD and risk factors. Although identified genetic associations have small effect sizes individually, polygenetic risk score (PRS) can combine such individual effects into a much stronger predicter of a disease trait. A few studies have shown the successful identifications of CAD and relevant traits. Earlier studies of PRS showed that the European ancestry-based can be transferred in other ancestry groups including South Asians, the associations of European ancestry-derived PRS were typically weaker in non-European ancestries. With large GWAS results from multiple ancestry groups, the PRS can be optimized to present ancestry-specific genetic risk for CVD.  A study of 7,244 South Asian UK Biobank participants derived a PRS of CAD for South Asians from the previous GWAS findings that are primarily European-based. The PRS included 6,630,150 common variants, and demonstrated a successful framework for developing ancestry-specific PRS.[63] In another study, researchers identified significant association between the GRS, which comprised of 29 genome-wide significant blood pressure variants found among European descent, and blood pressure among South Asians.[54]"2. Since the narrative review is cursory, it is not clear how the authors envision “multi-omic” methodologies should be deployed in South Asian populations. What are the key research questions with these methods in the South Asian population? What do the authors hypothesize will be found? Are there any characteristics specific to the South Asian population that should be accounted for ? Addressing these questions seems important for this review to understand how longitudinal multi-omics might “shed light” on CVD in South Asians.We appreciate reviewer’s suggestion. We included a new section of “The multi-omics approach may address several challenges in CVD research facing South Asians” to discuss three main research questions as initial examples for future multi-omics research in South Asians as below: "South Asians are an understudied population at high CVD risk even at low body weight and young ages, with a high propensity to diabetes, dyslipidemia, and hepatic steatosis, features that may provide new insights into CVD risk in the presence and absence of traditional risk factors. Given the genetic and molecular underpinning of CVD and risk factors, the genetic and molecular markers identified from multi-omics research may help accurately profile the CVD risk, given the unique characteristics among South Asians. Secondly, the multi-omics approach also holds the promise of revealing the heterogeneous mechanisms of CVD and risk factors. For example, HFpEF patients can be clustered into distinct subclasses with different clinical outcome using available demographic and clinical variables. T2DM is also a multi-factorial disease that involves numerous genetic pathways and many environmental factors,[134] and has high prevalence in South Asian populations. Recent studies of T2MD subgroups have revealed striking heterogeneity of T2DM risk, etiology and outcomes, which may be further illustrated by multi-omic profiling. Lastly, multi-omics can help explain inter-individual variability in response to environmental risk exposures. Exposures to environmental risk such as air pollution (common and severer CVD risk in South Asia) are multifactorial and time-varying, thus, their measurements can be incomplete, costly, and imprecise for pathophysiological effects. Omic technologies such as epigenomics and metabolomics represent exogenous and endogenous effects related to CVD risk and have emerged as key components of exposome measures. They can capture the biological response to environmental exposures, thus, providing more precise risk assessment for subclinical and clinical CVD. Improved omics measurements of environmental exposure will also enable large scale gene-environment interaction study to further uncover molecular mechanisms underlying CVD pathophysiology."  "In addition to common genomic and multi-omics factors of CVD across ancestry groups, studying multi-omics among large population samples within South Asians may also discover genetic variants or molecular signatures unique for South Asians. Incorporating these multi-omic profiles can optimize the diagnosis, treatment and prognosis of CVD, which is the most important and still growing health burden for South Asian populations."3. Are longitudinal -omics a component of research in other (including European ancestry) populations? What insights have been gained from such work? The authors suggest a longitudinal -omics approach in their concluding paragraphs, but have inadequately supported the potential merits of this strategy.Unlike the genome profile, epigenomic, transcriptomic, proteomic and metabolomic profiles can be modified by environmental exposures, physiological conditions and disease status. The need for longitudinal multi-omics includes two components. First, current omics studies predominantly use a cross-sectional design, which enables the novel biomarker discovery but is limited to infer causal associations due to confounding and reverse causation. A longitudinal design including baseline omics and incident CVD would better demonstrate the prediction utility of omics markers for CVD progression, and has been implemented in omic association studies in other ancestry groups. Secondly, repeated measurement of omics profiles excluding genomics would be important to understand long-term risk and natural history of chronic diseases (PMID 22424236) such as CVD, since these omics layers can capture the varying environment and pathobiology related to CVD development. Such omics changes may also help identify reversible targets for novel interventions for CVD outcomes. However, the multi-omics study with repeated measures hasn’t been reported for CVD. We added the following discussion to illustrate the need for longitudinal multi-omics in CVD research in the section of “The multi-omics approach is critical to understand CVD risk at the molecular level” as below: "Unlike the genome profile, epigenomic, transcriptomic, proteomic and metabolomic profiles can be modified by environmental exposures, physiological conditions and disease status. Genomic data will complement epigenomic and metabolomic markers by identifying complex biological processes at the systems levels.[116] Current omics studies predominantly use a cross-sectional design, which enables the novel biomarker discovery but is limited to infer causal associations due to confounding and revers causation. A longitudinal design including baseline omics and incident CVD would better demonstrate the prediction utility of omics markers for CVD progression, and has been implemented in omic association studies in other ancestry groups. However, such a design doesn’t incorporate the longitudinal changes of omics markers in relation to varying environment, pathobiology and disease progression. Repeated measurements of omics profiles excluding genomics would be important to understand long-term risk and natural history of chronic diseases[117] such as CVD. Such omics changes may also help identify reversible targets for novel interventions for CVD outcomes."4. This review would be a prime opportunity to move this field forward beyond only stating that these -omics tools should be applied in South Asian populations. What are the existing challenges/barriers preventing these tools from being implemented in the study of South Asian CVD and CVD risk?  What strategies would help overcome these barriers? The authors are recommended to consider addressing these questions in their review to provide important context to the state of the science and a roadmap to achieve their recommended future directions.We appreciate the suggestion. We revised the manuscript to address existing challenges and barriers for implementing multi-omics studies in South Asians in “Conclusion” section as below: "Despite the available tools and fruitful research conducted among European ancestry, the implementation of similar research among South Asians remains challenging. Large high-quality studies are needed, with the requirements of high volume recruiting of population-based study samples, well-defined disease and phenotypes, long time follow-up, establishment of data registries, close collaborations between scientists with various expertise, such as study design, molecular biology and bioinformatics. There is a growing effort of research among the South Asian population, such as the Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) study,[137] which is a large longitudinal study of 28,000 subjects across three large cities in South Asia. Studies that employ the integrative multi-omic approach to disentangling complex molecular systems underlying CVD are still anticipated."5. The authors’ concluding paragraph introduces new concepts that were not previously discussed . Consequently, their conclusions seem to be obscured and do not follow from their narrative. I recommended discussing these components of research gaps in South Asians earlier in the review, in order to justify their conclusions.We included background of HFpEF heterogeneity and the role of gene-environment interaction in the “Introduction” section as below. We also discussed the research gaps in a new section in response to comment #2. "Nearly half of the HF patients have HFpEF, with >90% being >60 years old, with rapidly increasing numbers.[32-35] Although numerous risk factors for HFpEF have been identified including hypertension, older age, female sex, obesity, diabetes, and renal disease, there are currently no class I guideline recommended treatments for HFpEF that improve mortality. HFpEF has received increased attention since HFpEF patients frequently experience delayed diagnosis and have limited treatment options. Recent studies have shown that HFpEF is a clinically heterogeneous disorder, consisting of subgroups with related comorbidities and pathophysiologies, which lead to different progression trajectories. Employing latent class analytics and clustering techniques based on widely available clinical variables, several investigators have shown that patients with HFpEF can be divided into distinct classes with differing outcomes. " "CVD progression can be affected by both gene and environment via different molecular pathways and mechanisms. Although the high throughput technologies have enabled accurate and cost-effective genotyping in large population samples, comparable high throughput measurements of environmental exposures are needed for large population studies. Gene-environment interaction is a common mechanism to explain complex disease risk, and inter-individual variability. Better understanding of gene-environment interactions and their causal relationships will point to pathways and mechanisms as potential targets for treatment and intervention. The gene-environment interaction study may also help understand the CVD risk among immigrant populations exposure to different environmental and lifestyle factors." The title of this review is missing leading. When I read the title ‘Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light’ I thought this review summaries omics research of CVD and risk factors in South Asia. But the paper mostly based on participants of European origin. Therefore, this is really a perspective of future research in Asia. The title is not appropriate.I suggest the paper comprehensively summarized the research publications in the field. For example, for blood pressure GWAS, the paper cited 2011 GWAS. There are at least 4 GWAS publications after 2015. For DNA methylation, there are many papers with larger sample sizes published after 2015. But this paper only included a few for CVD risk factors. If talking about multi-omics, the paper should also include publications of CVD and risk factors with proteomics and gene expression/RNA seq.I also suggest the co-authors include a table summarize the resent publications for CVD outcomes and risk factors.Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes and hyperlipidemia over the last two decades. A thorough understanding of CVD-associated omics profiles may lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health in South Asia. However, I don’t think this review provided a comprehensive review for multi-omics study of CVD and risk factors. Below is the summary of my comments.Is the review written in accessible language?YesAre all factual statements correct and adequately supported by citations?YesAre the conclusions drawn appropriate in the context of the current research literature?YesIs the topic of the review discussed comprehensively in the context of the current literature?PartlyReviewer Expertise:Statistical genetics and genomics.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. 1. The title of this review is missing leading. When I read the title ‘Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light’ I thought this review summaries omics research of CVD and risk factors in South Asia. But the paper mostly based on participants of European origin. Therefore, this is really a perspective of future research in Asia. The title is not appropriate.The reviewer is correct about the perspective component of the manuscript because the multi-omics research of CVD is still limited, particularly among South Asians. Meanwhile, the prevalence of heart failure and atherosclerotic heart disease in South Asian populations is rising, and the incidence is higher at younger age and leaner body mass index in South Asians compared to European population. The growing evidence from epidemiologic studies emphasizes the importance of improving cardiovascular health among South Asians. Therefore, we acknowledge that the current omics research of CVD is primarily conducted among European population, and address the needs for such omics studies in South Asians. We also noted a recent genetic study of coronary heart disease, which demonstrated the predictive ability of polygenic risk score in South Asians (PMID 32762905). As a result, we hope the title represents the current knowledge of CVD in South Asians, multi-omics of CVD (mostly in European ancestry) and anticipation for the future efforts in tackling the disparity in South Asians, a mixture of review and perspective in the present manuscript. 2. I suggest the paper comprehensively summarized the research publications in the field. For example, for blood pressure GWAS, the paper cited 2011 GWAS. There are at least 4 GWAS publications after 2015. For DNA methylation, there are many papers with larger sample sizes published after 2015. But this paper only included a few for CVD risk factors.We appreciate the reviewer’s suggestion on including recent publications of large GWAS and DNA methylation studies. We included recent blood pressure GWAS with larger sample sizes , in addition to the 2011 blood pressure GWAS as an early multi-ethnic GWAS including South Asians (PMID 21909115). We also added recent multi-ethnic GWAS publications of CVD and risk factors, including coronary heart disease , heart failure , type 2 diabetes (PMID 32541925), BMI (PMID 30124842), and blood lipids (PMID 30275531). The revised text under “Genetic basis of atherosclerotic cardiovascular disease and heart failure” is listed below: "Genome-wide association studies (GWAS) have identified a large number of genetic loci associated with coronary heart disease,[42-44] ASCVD,[45-47] HF, and their risk factors, such as BMI, blood lipids, blood pressure,[54-57] and T2DM;[58] however, these genetic variations explain only a small portion of risk in populations."When reviewing the epigenome-wide association studies (EWAS), we focused on studies with prospective design and potential causal inference. For example, the Agha 2019 study (PMID 31424985) discovered CpG sites associated with incident coronary heart disease or myocardial infarction, and the Mendelian Randomization analysis revealed the causal effect of DNA methylation sites in the disease mechanism. The Westerman’s 2019 paper (PMID 31615550) also discovered DNA methylation modules associated with incident cardiovascular disease. Additionally, we included several large EWAS of CVD risk factors, including type 2 diabetes , BMI (PMID 28002404), blood lipids (PMID 28194238) and blood pressure . The revised text under “Epigenetic signatures identify molecular pathways of CVD that are activated in the context of environmental risk” is listed below: "EWAS provides an unbiased approach for identifying molecular mediators of genetic and environmental factors that may explain residual risk of disease[74] and has been applied to investigate CVD[75-79] and risk factors.[80-85]" "The study of incident T2DM conducted among Indian Asians and Europeans showed a 2.5 times higher adjusted risk among Indian Asians than Europeans, and five loci including ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP were associated with incident T2DM among Indian Asians and replicated among Europeans.[81] The other study of incident T2DM reported additional loci such as PHGDH and CPT1A, which were discovered among Europeans and replicated among Indian Asians.[80] The study of blood pressure compared the methylation profiles between Europeans and South Asians revealed many distinct loci between the two ancestries with a small overlap.[84] To our current knowledge, some known trans-ethic epigenetic loci might be transportable from Europeans to South Asians, but there is still a lack in studies specifically among large South Asian populations to further explore novel loci to explain the higher risk. A number of EWAS have examined DNAm patterns associated with air pollution, which is a known environmental risk factor for CVD."For the multi-omics studies, we included a recent publication that integrated genome-wide single-nucleotide polymorphisms, gene expression, and DNA methylation, revealed the molecular mechanism of heart failure (PMID 31703168), and another study of CVD (PMID 33836805). The revised text under “The multi-omics approach is critical to understand CVD risk at the molecular level” is listed below: "A recent study using longitudinal big data including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring have showed the potential of revealing cardiovascular pathophysiology on a molecular basis.[118] Although increasing number of population studies have measured multi-omics data, recent studies have focused on single -omic association study and used additional -omics data to better understand the molecular functions of identified associations.[119] Integrated multi-omics studies of CVD outcomes have been limited. A large HF study of over 8,000 participants within the Framingham Heart Study utilized integrative trans-omics data including genetic variations, DNA methylation, and gene expression data to reveal genetic contributions towards HF. The transportability of such findings to South Asians needs to be evaluated.[120] Another study integrating DNA methylation and gene expression data identified independent latent factors associated with CVD. The unsupervised machine learning of multi-omics successfully improved classification and discrimination.[121]"3. If talking about multi-omics, the paper should also include publications of CVD and risk factors with proteomics and gene expression/RNA seq.We appreciate the suggestion. We have added a paragraph summarizing “Proteomics and gene expression reveal the interactions between cell processes and external environment”. The text under this section is listed below: "The proteomics technologies have evolved rapidly in the past two decades. Recent applications of proteomics in population studies have produced interesting findings in CVD research.[99] A recent study of the healthy human heart tissue collected from autopsy determined the healthy heart proteome. The resulted database, which included over 10,700 proteins, is a comprehensive resource for the downstream investigations.[100] In a targeted proteomics study, two protein signatures for high-risk plaques and absence of coronary atherosclerosis were identified among a cohort with suspected coronary artery disease.[101] The prediction accuracy of a model constructed by 50 proteins showed a better prediction accuracy in adverse cardiovascular events than a traditional risk factor model.[102] These findings are critical in CVD risk prediction and differentiation of CVD subtypes. In addition, gene expression profiling in CVD also enables a better understanding of pathophysiology of CVD.[103] Patterns of gene expression of human aorta tissue was investigated to identify genes with prediction power in atherosclerosis.[104] Studies of non-coding transcriptome, which even though have limited protein-coding functions, are discovering the pathology of CVD. To eventually realize precision medicine, we are still facing the challenges of standardization of methodologies and translation.[105] In addition, researches in this area largely depend on the availability of tissues from autopsy, thus the clinical translation and implementation has been limited. However, such studies facilitate a better understanding on the disease causal pathway and mechanism. Particularly, there has been a lack of similar researches particularly among South Asians, which is urging the future efforts of investigation."4. I also suggest the co-authors include a table summarize the resent publications for CVD outcomes and risk factors.We appreciate the suggestion. As we focused on the CVD outcomes in South Asians, we added a summary table (Table 1) for recent omics studies of CVD including coronary artery disease, stroke, myocardial infarction and heart failure, particular in multi-ethnic studies when available. We also added text in the “Introduction” section.


Epidemiological evidence for specific long-term conditions is required to inform best practices regarding the substantial health inequalities experienced by sexual minority individuals compared with heterosexual peers.To describe inequalities in long-term conditions among sexual minority  adults.Cross-sectional analysis of 1 341 339 nationally representative survey responses from the English GP Patient Survey (GPPS).Stratifying by sex, the weighted prevalence and covariate-adjusted association of 15 long-term conditions were calculated, comparing sexual minority and heterosexual adults, considering variation by sexual orientation and variation in sexual orientation inequalities by deprivation, ethnic group, region, and age.After adjusting for deprivation, ethnic group, region, and age, 13 long-term conditions  were more prevalent among sexual minority women than their heterosexual peers, with the largest inequalities for mental health problems , neurological conditions , dementia , and back problems . It was found that nine long-term conditions were also more prevalent among sexual minority men including mental health problems , 'all other conditions' , neurological conditions , and kidney or liver disease ; inequalities were often largest for bisexual adults. Inequalities did not vary significantly by deprivation, ethnic group, or region except for mental health problems. Inequalities in multimorbidity were highest at younger ages; for example, LGB women aged 18–24 years had multimorbidity at the same level (approximately 20%) as heterosexual women aged 45–54 years.Sexual minority adults, especially bisexual adults, are at elevated risk for many long-term conditions and multimorbidity; this risk spans socioeconomic status and ethnic group, representing a significant healthcare challenge. Sexual minority individuals experience poorer health; this work provides new evidence that most of the 15 long-term conditions examined occur more frequently among sexual minority adults in every age group. The large sample size of this study helps identify the specific conditions and ages for which risk is greatest. Multimorbidity for sexual minority adults is a significant healthcare challenge, with levels of multimorbidity associated with middle-age often found in young sexual minority adults. Primary care is central to addressing these inequalities; the holistic person-centred clinical approach of GPs will be central to reducing disparities in health outcomes. Despite higher disease burdens, LGB adults face barriers to healthcare access and have poorer primary care experiences. The 2010 UK Equality Act improved the collection of sexual orientation information in survey data, but adequate sample sizes for research on multiple long-term conditions remains challenging. Therefore, data were used from the GPPS, which provides a large , nationally representative (of the population registered with a GP in England) sample to describe inequalities in long-term conditions, defined as a difference or variation in the prevalence of a long-term condition. In this analysis LGB options for sexual orientation were included from GPPS (gender identity was not measured).Lesbian, gay, and bisexual (LGB) adults in the UK experience poorer health and access to health care than heterosexual women and men.In the first analysis, whether long-term conditions were elevated for LGB, compared with heterosexual adults, was considered. In the second, whether inequalities continued to exist after adjustment for deprivation, ethnic group, and age, and whether there was variation among LGB women and men. Variation in the association between sexual orientation and long-term conditions by deprivation, ethnic group, and age was additionally tested. Finally, inequalities experienced by sexual orientation were explored across all conditions included in the analysis, and whether levels of multimorbidity vary by age. Collectively, these steps provided a detailed portrayal of the health inequalities in long-term conditions experienced by LGB adults in England.Data were analysed from the GPPS; a cross-sectional survey of adults registered with a general practice between July 2015 and March 2017 in England.Responders were asked, 'Which of the following best describes how you think of yourself?' with response options 'Heterosexual or Straight', 'Gay or Lesbian', 'Bisexual', 'Other', and 'Prefer not to say'. The 'Prefer not to say' responses were excluded. 'Sexual minority adults' hereafter refers to 'Gay or Lesbian', 'Bisexual', and 'Other'.Responders were asked, 'Which, if any, of the following medical conditions do you have?' with 15 response options , plus 'NIn multivariable analysis, deprivation, ethnic group, region, and age were adjusted for and all analyses were stratified by sex.'Multimorbidity' was measured as reporting at least two of the 15 conditions, and a count of the 15 conditions ('condition count') was additionally estimated.Across the 2015–2016 and 2017 survey waves, 4 306 560 surveys were mailed with 1 644 644 responses (response rate 38.2%). Surveys were excluded with missing data for long-term conditions, age, or sex (8.4%), or missing or ‘Prefer not to say’ responses to the sexual orientation question (8.0%). Missing long-term condition responses were similar for sexual minority and heterosexual responders. these cross-sectional weights cannot be combined across years. For adjusted unweighted multivariable analyses, data were also included from the 2015–2016 fieldwork period, as the sampling frame excludes people who were surveyed in the previous 12 months.Unadjusted prevalence estimates from the January–March 2017 fieldwork period used three-part survey weights ;The first analysis described the 2017 weighted prevalence of the 15 long-term conditions among heterosexual and sexual minority women and men  for eight conditions for women and 13 conditions for men. Where there is evidence of heterogeneity, the OR is most often largest for the bisexual group, among both women and men.The third analysis examined differences in the sexual minority and heterosexual long-term condition gap by deprivation, ethnic group, region, and age. Except for mental health problems, there was no systematic evidence of heterogeneity by deprivation, ethnic group, or region (see Supplementary Table S3). There was, however, evidence of heterogeneity by age. For many conditions, the additional risk associated with sexual minority status was greater at younger ages , especiaThe fourth analysis summarised multimorbidity differences by sexual minority status. Sexual minority adults were more likely to be living with multimorbidity (≥2 conditions) than heterosexual adults of the same ages, with inequalities largest at youngest ages . For exa unadjusted comparisons of the prevalence of long-term conditions understate the burden on sexual minority adults of conditions that primarily emerge at middle and older ages. After adjusting for deprivation, ethnic group, region, and age, most long-term conditions were more prevalent among sexual minority adults; bisexual adults often had the highest risk. The magnitude of the inequalities facing sexual minority adults generally did not vary by deprivation, ethnic group, or region, but gaps tended to be larger at younger ages. Young sexual minority adults, especially young sexual minority women, were much more likely to be living with multimorbidity.This analysis provides new evidence regarding inequalities in long-term conditions for sexual minority adults in England. Because the sexual minority population is substantially younger than the heterosexual population,The large, nationally representative, population-based sample with repeated cross-sectional waves over time are the greatest strengths of this research, enabling comparisons of sexual orientation inequalities by demographic characteristics and sexual orientation subgroups that are rarely available. The examination of 15 long-term conditions in the same, large sample enabled comparisons of the disparities across conditions that would not otherwise be possible. and survey response rate alone is a poor measure of bias; predictors of low response rates  are adjusted for in these analyses. Further, a randomised trial of the inclusion of a sexual-orientation question in GPPS found no impact on survey response rates in England. Another limitation to this research is the use of a self-reported measure of long-term conditions. The performance of this survey question has been evaluated in previous research, with prevalence estimates similar to other national health surveys in England, and the use of self-reported rather than clinically-coded diagnoses may better reflect a patient-centred measure of the impact of multimorbidity. Although a study of electronic healthcare records might provide more detailed insight into long-term conditions, the limited documentation of sexual orientation in healthcare records means that surveys remain the best way to understand health inequalities among sexual minority adults. There is no reason to believe that the shortcomings of self-reported measures of long-term conditions differ by sexual orientation, so this would not be expected to bias such comparisons. Finally, the survey did not include a question about HIV. It is possible but cannot be confirmed that this may be captured by the high prevalence of 'another long-term problem' among sexual minority men.Non-response remains the primary challenge to the validity of findings in survey research focused on sexual orientation-based inequalities; the impact of non-response on GPPS has been evaluated previously, Collection of gender identity in the 2021 census may provide opportunities to address this evidence gap.Inequalities experienced by transgender adults in primary care were not described in this analysis as this was not measured in GPPS. Transgender people often face distinct challenges in clinical encounters associated with their gender identity, ranging from inappropriate use of pronouns to issues around the management of hormone and surgical treatment. The finding that neurological conditions (including dementia and epilepsy) are particularly over-represented, to the authors' knowledge, have not previously been reported in large epidemiological analyses.These results are consistent with previous studies highlighting the high prevalence of individual long-term conditions among sexual minority adults. Further, all sexual minority adults, regardless of deprivation or ethnic group, face elevated risk of long-term conditions; this finding is difficult to compare with previous studies that lacked the sample sizes to make such assessments possible.These results are consistent with research documenting especially negative health outcomes for bisexual adults that may be related to their simultaneous isolation from sexual minority and heterosexual communities. Research has shown how sexual orientation disclosure during early adulthood can often have a substantial short-term negative impact on mental health, with positive long-term benefits. Further, studies document how negative experiences in childhood among sexual minority adults have a lasting impact on their mental health; previous research has found that multimorbidity is independently associated with a history of adverse childhood experiences. In this analysis, inequalities are highlighted across long-term conditions, including mental health, suggesting the widespread health impact experienced by sexual minority people across their lifespan.This analysis found that sexual minority adult inequalities are greatest when multimorbidity is less common at younger ages. The unique health impacts of specific challenges experienced by sexual minority young adults are increasingly recognised. these findings highlight the importance of this area. While management of long-term conditions in primary care is not specific to sexual orientation, provision of high-quality primary care is central to improving the health and health-related quality of life of people with long-term conditions and multimorbidity. This work highlights that young sexual minority adults have disproportionately higher inequalities in long-term conditions, and so are a particularly important group to consider.Healthcare delivery for sexual minority adults has historically not focused on long-term conditions; these results confirm the importance of such an approach.Inequalities exist across many long-term conditions, highlighting the importance of a holistic, integrated approach to the management of long-term mental and physical health conditions in addressing the health inequalities experienced by sexual minority adults. In 2018, the UK Government Equalities Office developed an LGBT Action Plan, which highlighted the value of integrated LGBT care in physical and mental health services; higher alcohol intake, and higher body mass index, especially among sexual minority women, compared to heterosexual adults; these conditions are most often addressed and managed in primary care, which further underscores the potential role for GPs and practice staff.Additionally, given that these inequalities are not limited to a small cluster of long-term conditions, the results also imply that more general approaches, such as a focus on prevention and healthcare delivery, may be more effective than disease-specific approaches in addressing these health inequalities. Preventive medicine is a key area where the results have implications for primary care. The lower measured, unadjusted prevalence for sexual minority women for hypertension and cancer, conditions that often do not present with symptoms, may reflect less screening and primary care use, rather than lower risk; if so, it identifies a need to be addressed. Sexual minority adults are more likely to have a smoking history, targeted improvements for sexual minority adults may be important. Recent guidance and training for GPs from the Royal College of General Practitioners included a focus on LGBT patients. The LGBT Foundation Pride in Practice programme is another resource highlighting the effectiveness of small changes, such as LGBT posters on notice boards. Better supporting the disclosure of sexual orientation in primary care consultations may also have the potential to improve health and healthcare outcomes. For example, lesbian and bisexual women access less cervical screening; disclosure of sexual orientation in primary care consultations may reduce these inequalities through improved uptake of preventive care.Given evidence of poorer primary care experiences, The proposal was meant to improve both research and practice: the routine collection of sexual orientation by GPs would allow better monitoring of inequalities and simultaneously support sexual orientation disclosure. Despite these advantages, the proposed rollout of sexual orientation questions and recording of sexual orientation in clinical records remains low and requires further attention. Giving the public confidence in how their data are used by ensuring that data are secure and used appropriately, with clear public benefits, is an important first step.With support from LGBT organisations, NHS England advocated for the inclusion of sexual orientation monitoring in 2017.This analysis presents population-based evidence on inequalities in long-term conditions experienced by sexual minority adults and suggests that although physical health is often separated from mental health, considering both is needed to more effectively address the pervasive inequalities experienced by sexual minority adults of all ages across a range of long-term conditions. Evidence of early multimorbidity means that GPs should pay particular attention to prevention, screening, and care for long-term conditions in their sexual minority patients, even in early adulthood.


Based on a review of recent literature, a recurrent circuit model describes how cortico-thalamo-cortical and cortico-cortical circuitry supports word retrieval, auditory-verbal comprehension, and other language functions. Supporting data include cellular and layer-specific cortico-thalamic, thalamo-cortical, and cortico-cortical neuroanatomy and electrophysiology. The model posits that during word retrieval, higher order cortico-thalamo-cortical relays maintain stable representations of semantic information in feedforward processes at the semantic-lexical interface. These stable semantic representations are compared to emerging lexical solutions to represent the semantic construct to determine how well constructs are associated with each other. The resultant error signal allows cortico-cortical sculpting of activity between the semantic and lexical mechanisms until there is a good match between these two levels, at which time the lexical solution will be passed along to the cortical processor necessary for the next stage of word retrieval. Evidence is cited that high gamma activity is the neural signature for processing in the cortico-thalamo-cortical and cortico-cortical circuitry. Methods for testing hypotheses generated from this recurrent circuit model are discussed. Mathematical modeling may be a useful tool in exploring underlying properties of these circuits. Lesions in the left ventral anterior thalamus, which generally are ischemic, almost always result in aphasia acutely characterized by semantic paraphasias often deteriorating into semantic jargon with intact repetition and variability of other symptoms. Left pulvinar lesions, which generally are hemorrhagic, result in semantic paraphasias, fluent output, intact repetition, and comprehension less impaired than the pattern of output would suggest for cortical lesions Crosson, . As a ruSix years ago, a reconsideration of thalamic mechanisms in language was published based on advances regarding thalamic mechanisms prior to 2012 Crosson, . That trHowever, one unresolved conundrum arising from these conclusions is what purpose cortico-thalamo-cortical information transfer serves when direct cortico-cortical circuitry exists  These pyramidal neurons are more prominent in cortical layer 5b than in layer 5a  the connectivity between layers within a cortical area that defines cortical columns (intra-area connectivity), and (2) the connectivity between cortical areas that defines cortico-cortical connectivity (inter-area connectivity).tend to promote rapidly adapting change in firing patterns. In other words, cortico-thalamic circuitry is biased toward maintaining information encoding in firing patterns, while cortico-cortical circuitry is biased toward change in information processing  rhythm generator. Just as the idea of the thalamus as a relay from periphery to cortex is giving way to the inclusion of higher-order cortico-thalamo-cortical relays  and lower fidelity (nonlinear) firing modes? Some regulatory mechanism is needed to allow switching from one concept to another as lexical-semantic processing proceeds. As we noted above, cortical layer 6 input to the thalamus is thought to change the state of target thalamic relay neurons from a low-fidelity to a high-fidelity transfer mode, where output is linearly related to the driving input. In higher order relays, such as those involved in language, this driving input to the thalamic relay cells comes from layer 5 neurons  to the pulvinar and ventral anterior nucleus of the human thalamus . As a result, they substitute semantically related words for the target word  cortex, which is the opposite direction from sensory processing, which moves from primary to higher-order cortex (as noted above). Specifically addressing the semantic-lexical interface relevant to word finding in thalamic aphasia, the left inferior frontal gyrus (LIFG) has long been considered critical for language production. Some evidence indicates anterior to posterior processing gradient, with the anterior LIFG more involved in processing the semantic properties and the posterior LIFG in processing the phonological properties of words  or only rudimentary (dysgranular) layer 4 in some frontal cortices. Pars triangularis is considered eulaminate cortex , but pars opercularis is considered dysgranular cortex  are much more common than other errors Crosson, . FinallyThis paper has focused on the role of higher-order thalamic relays  in language processing. We have accomplished this goal primarily through inductive reasoning. Specifically, we have used both neuroanatomical and neurophysiological findings from animal model studies, as well as recent modifications of a long-standing conceptual framework Hebb,  to buildIn this regard, the model also should be able to explain why repetition usually is less impaired than other language functions in thalamic aphasia Crosson, , 1992. TOne potential weakness in the current model is the use of animal model data to infer mechanisms in a uniquely human function like language. For example, the specific information regarding at what cortical level cortico-cortical and cortico-thalamic pyramidal cells communicate was derived from rodent frontal and somatosensory cortices (Kawaguchi, In our description of the recurrent circuit at the semantic-lexical interface as a model for the functional role of higher-order thalamic relays in language, many readers probably have developed questions that could be tested in animal models. Yet, the purpose of the model is to explain phenomena related to language, a uniquely human function, and to generate further hypotheses within that realm. Hence, we will focus our closing remarks on future research directions regarding thalamic functions in language, which by definition must be tested in the human realm. Because of the limitation of methods available for use in humans, this endeavor can be challenging. For example, opportunities for doing recording from individual neurons are rare in humans, and opportunities for recording local field potentials are driven by the clinical need for such recordings. Nonetheless, hypotheses from the current model can be generated that are amenable to testing at a more macroscopic neural systems level using functional neuroimaging. Good examples of this kind of research do exist in the literature. For instance, Kraut, Hart and their colleagues (Kraut, Calhoun, Pitcock, Cusick, & Hart Jr., Another issue requiring further attention is why patients with lesions confined to the thalamus recover relatively rapidly. One possibility, specific to polar artery infarcts, is that the lesion is near a critical pathway between frontal cortices and the pulvinar. Bohsali et al.  traced tIn closing, this neurocognitive model can provide a framework to develop hypotheses for future research, including lesion studies. A few conceptually driven studies exist in the literature (e.g., Mennemeier et al.,


Cardiovascular magnetic resonance (CMR) is a radiation-free, high-spatialresolution technique which provides dynamic assessment of the heart andpericardial tissue. This is particularly useful for the evaluation andcharacterisation of non-cardiac tumours close to the pericardium for theexclusion of cardiovascular infiltration, and also for the assessment of theextent of myocardial invasion of cardiac metastases. This information can helpmake key decisions on further management in oncology multidisciplinary meetings.The CMR evaluation and main types of sequences acquired are detailed in thiscase series to illustrate the application of CMR in the assessment ofnon-cardiac malignancies and its importance in guiding management. A particular benefit of CMR is in the determination of cardiovascularinfiltration, which can be difficult to assess on other imaging modalities. Theresults of the CMR scan often provide the decisive information in oncologymultidisciplinary meetings (MDMs) for subsequent management. In addition, with theappropriate sequences and selection of the desired imaging planes, it can provideexcellent anatomical detail to help with surgical planning for tumours close to butno invading the heart. Being radiation-free CMR, is frequently adopted as thepreferred imaging modality for follow-up, especially in young adults.Cardiovascular magnetic resonance imaging (CMR) is a radiation-free imaging modalityable to provide anatomical detail, accurate assessment of myocardial volumes andfunction, tissue characterisation and dynamic assessment of the heart andpericardial tissue. CMR offers imaging of the heart in any desired imagingplane.6,7 These will be discussed indetail in this case series. Absolute contraindications such as metallic foreignbodies, or non-MR compatible pacemakers are important safety checks prior to any MRIscan.Some limitations of CMR imaging include the long acquisition time when compared toCT, end-stage renal failure and claustrophobia. However, in these situations,sometimes a time-saving single sequence, or a non-contrast mapping sequences suchthe T1 and T2-mapping, is adequate to answer the clinical question.In this case series, we review clinical scenarios in which CMR was used in theevaluation of non-cardiac malignancies to determine cardiovascular involvement. Themain objectives are to illustrate CMR protocols, interpretation of the findings, andthe role of CMR as an important adjunct to other imaging modalities in clarifyingthe diagnosis.CMR can offer invaluable information for the diagnosis and treatment planning ofextra cardiac masses or cardiac metastases. More specifically, CMR can providedetailed tissue characterisation, evaluation of vascularity and perfusion of a mass,and assessment for the presence and extent of tissue invasion. Masses should beidentified in at least two orthogonal planes and delineated further with differentsequences that demonstrate tissue characteristics, using the imaging planes thatbest visualise the lesion.T1 weighted and T2weighted imaging with fat suppression, early and late gadolinium enhancementimaging. These are useful for localisation, assessment of morphology and margins ofthe mass, tissue characterisation and evaluation of tumour extension andvascularity. Cine imaging also provides assessment of ventricular function andpossible evidence of compression of a cardiac chamber from a mass or due to thepresence of pericardial effusion. Early and late gadolinium imaging can identifythrombi inside the heart, as well as scarring or areas of necrosis inside a mass orof the ventricular walls. Although still not widely used and comprehensivelyevaluated in cardiac or extra cardiac masses, T1- and T2-mapping can add detailedtissue characterisation, without contrast administration.6,7 T2 mapping can provide further informationabout myocardial oedema. Information from parametric mapping techniques can also bedisplayed as colour maps to facilitate visual interpretation. First-pass perfusionimaging can also be added to the protocol to assess the vascularity of a mass andthe risk of bleeding during resection. Finally, CMR tagging sequences can be used inthe assessment of the pericardium in cases of unclear mass invasion or infiltration.Of course, the CMR protocol can be adjusted and tailored to the specific mass underinvestigation.A complete CMR protocol includes anatomical imaging of the entire thorax, cineimaging usually using steady-state free precession (SSFP sequences),A 36-year-old female with a history of right tibial synovial sarcoma treated withabove knee amputation was found to have a large right ventricular mass onroutine echocardiography prior to commencing chemotherapy. CT confirmed anill-defined low-density mass within the right ventricle  which shde novo atrial fibrillation. Her past medicalhistory included neurofibromatosis Type 1 with multiple resections of relatedtumours including: left knee myxofibrosarcoma, malignant peripheral nerve sheathtumour of the scalp, gastrointestinal stromal tumour and carcinoma of the leftbreast. Investigation with computed tomography pulmonary angiogram (CTPA) showeda filling defect in the right atrium  as the mesenteric fat, intra-and extrathoracic fat  compared tonon-contractile tumour tissue. Other CMR acquisitions such as theThis case series used clinical scenarios from the oncology MDMs to illustrate theappropriate use of CMR to answer difficult questions about cardiovascularinvolvement of extracardiac tumours adjacent to the heart, or the extent ofmyocardial involvement and resectability of metastatic cardiac tumours. The CMRfindings were not only important to guide the decision-making process, but alsoallowed for surgical planning and follow-up. For Case 3 and Case 4, thecardiothoracic surgeon specifically requested CMR prior to any surgical opinion,which was then followed by evaluation on a case-by-case basis at the MDM. When apatient is referred for CMR for these indications, we would recommend a discussionbetween the clinical team with the Cardiologist/Radiologist supervising the list toreview the clinical background, main clinical objective, and recent imaging to allowcareful planning of the scan particularly when only limited sequences can beperformed for patients who cannot tolerate the scan or are claustrophobic.CMR could provide clear delineation of the mass from the adjacent pericardiumand myocardium.CMR is an important imaging investigation for the exclusion of cardiovascularinvolvement from adjacent thoracic tumour.Time-saving sequences can be performed for patients who cannot tolerate thescan.