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The under‐representation of non‐European cohorts in neurodegenerative disease genome‐wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non‐European or multi‐ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non‐European or multi‐ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non‐European or multi‐ancestry studies. Notably, only six of the loci have been replicated. The significant under‐representation of non‐European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. Highlights Eighty‐two percent of neurodegenerative genome‐wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.

INTRODUCTION Most genetic studies for Alzheimer's disease (AD) have been focused on late‐onset AD (LOAD). There are no large genetic studies on early‐onset AD (EOAD). METHODS We performed a multi‐ancestry (non‐Hispanic European, African, and East Asian) genome‐wide association study (GWAS) including a total of 7,349 cases and 17,887 control. Cases with age at onset younger than 70 years were included. Sensitivity analysis including cases with onset <65 was performed. Only controls older than 70 were included to decrease the risk of developing LOAD. RESULTS We identified eight novel significant loci: six in the ancestry‐specific analyses and two in the trans‐ancestry analysis. By integrating gene‐based analysis, expression quantitative trait loci (eQTL), protein quantitative trait loci (pQTL), and functional annotations, we nominate eight novel genes that are involved in microglia activation, glutamate production, and signaling pathways. DISCUSSION EOAD, although sharing genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification. Highlights We performed the largest and first multi‐ethnic genetic screening for early‐onset Alzheimer's disease (AD). We identified eight novel significant loci: six in the ancestry‐specific analyses and two in the trans‐ancestry analysis. The novel genes are implicated microglia activation, glutamate production, and signaling pathways. EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.

INTRODUCTION Much of Alzheimer's disease (AD) risk is explained by age, apolipoprotein E (APOE) genotype, and sex. We sought to identify genetic modifiers of age at onset (AAO) of AD while probing the influence of sex and APOE among those with diverse ancestry. METHODS We performed genome‐wide association studies (GWASs) of AAO in two diverse samples followed by meta‐analysis, contrasting results with and without adjustment for sex and APOE. Genome‐wide significance was set to p < 5×10−8. RESULTS GWASs adjusting for sex, APOE, population structure, and relatedness revealed 17 significant loci including independent associations at AD risk loci and four novel signals. APOE adjustment influenced GWAS effect sizes across the genome while sex adjustment had minimal effect. DISCUSSION We identified association signals within a diverse but relatively small sample, replicating loci recently discovered in large European ancestry‐only GWASs, and illustrated the power of using a quantitative trait like AAO over a binary diagnosis trait. Highlights Survival analysis approach identified known and novel genetic modifiers of Alzheimer's disease (AD). Multi‐ancestry analyses revealed independent signals at known AD loci. Apolipoprotein E adjustment influenced variant effects across the genome.

INTRODUCTION Alzheimer's disease (AD) has genetic and environmental risk factors, including cigarette smoking. Gene–environment interactions may explain AD missing heritability. METHODS Lifetime smoking data from 22,032 European ancestry and 3126 African ancestry participants from the Alzheimer's Disease Genetic Consortium and the Framingham Heart Study were used to conduct genome‐wide single nucleotide polymorphism (SNP)‐by‐smoking interaction and smoking‐stratified association studies. For top‐ranked loci, brain‐derived bulk and single nuclei RNA‐sequencing were used for differential expression and colocalization analyses. RESULTS Among smokers only, there was a genome‐wide significant association in the APAF1/ANKS1B region (rs12368451; odds ratio = 1.19, 95% confidence interval: [1.12, 1.27], p = 3.0 × 10−8). Rs12368451 had expression quantitative trait locus (eQTL) activity that differed by smoking status and brain cell types but showed the most significant posterior probability (PP = 0.15) for being causal via ANKS1B expression in oligodendrocytes among smokers. DISCUSSION Potentially causal in smokers via eQTL activity, the top SNP may alter expression of ANKS1B, which encodes amyloid beta precursor protein intracellular domain associated‐1, known to regulate amyloid beta plaques. Highlights Among smokers only, a novel chromosome 12 single nucleotide polymorphism (SNP) near ANKS1B was associated with Alzheimer's disease. Evidence came from European and African ancestry cohorts. RNA‐sequencing analyses implicated the top SNP as causal via ANKS1B expression in oligodendrocytes. A genome‐wide African ancestry–specific significant SNP–smoking interaction was observed on chromosome 6 in SLC22A23.

INTRODUCTION An integrative polygenic risk score (iPRS) capturing the neurodegenerative and vascular contribution to dementia could identify high‐risk individuals and improve risk prediction. METHODS We developed an iPRS for dementia (iPRS‐DEM) in Europeans (aged 65+), comprising genetic risk for Alzheimer's disease (AD) and 23 vascular or neurodegenerative traits (excluding apolipoprotein E [APOE]). iPRS‐DEM was evaluated across cohorts comprising older community‐dwelling people (N = 3702), a multi‐ancestry biobank (N = 130,797 Europeans; 105,404 non‐Europeans), and dementia‐free memory clinic participants (N = 2032). RESULTS iPRS‐DEM was associated with dementia risk independently of APOE in the elderly (subdistribution hazard ratio [sHR]per1SD = 1.15, 95% confidence interval [CI]: 1.03 to 1.28), which generalized to Europeans (EUR‐sHRper1SD = 1.28, 95% CI: 1.09 to 1.51]), East‐Asians (EAS‐sHRper1SD = 5.29, 95% CI: 1.43 to 34.36), and memory‐clinic participants (sHRper1SD = 1.25, 95% CI: 1.11 to 1.42). Prediction was comparable to clinical risk factors in older community‐dwelling people, with improved performance among memory‐clinic patients. Risk stratification was enhanced by defining four genetic risk groups with iPRS‐DEM and APOE ε4, reaching five‐fold increased risk in APOE ε4+/iPRS‐DEM+ memory‐clinic participants. DISCUSSION Alongside APOE ε4, iPRS‐DEM may refine risk stratification for the enrichment of dementia clinical trials and prevention programs. Highlights iPRS‐DEM reflects neurodegenerative and vascular contribution to dementia. We show iPRS‐DEM captures additional dementia genetic risk beyond APOE and AD‐PRS. iPRS‐DEM, in combination with APOE ε4, shows promise for dementia risk stratification. Our results generalize across both population‐based and memory‐clinic settings. We show transportability of iPRS‐DEM to East Asian ancestry.

Purpose of ReviewType 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction.Recent FindingsRecent large-scale, multi-ancestry genetic studies of T2D have identified over 500 novel risk loci. The genetic variants (i.e., single nucleotide polymorphisms (SNPs)) marking these novel loci in general have smaller effect sizes than previously discovered loci. Inclusion of samples from diverse ancestral backgrounds shows a few ancestry specific loci marked by common variants, but overall, the majority of loci discovered are common across ancestries. Inclusion of common variant GRS, even with hundreds of loci, does not substantially increase T2D risk prediction over standard clinical risk factors such as age and family history.SummaryCommon variant association studies of T2D have now identified over 700 T2D risk loci, half of which have been discovered in the past 3 years. These recent studies demonstrate that inclusion of ancestrally diverse samples can enhance locus discovery and improve accuracy of GRS for T2D risk prediction. GRS based on common variants, however, only minimally enhances risk prediction over standard clinical risk factors.

Background Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in ancestry groups of predominantly non-European ancestral background in genome-wide association studies (GWAS). We construct and analyze a multi-ancestry GWAS dataset in the Alzheimer’s Disease Genetics Consortium (ADGC) to test for novel shared and population-specific late-onset Alzheimer’s disease (LOAD) susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6728 African American, 8899 Hispanic (HIS), and 3232 East Asian individuals, performing within ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. Results We identify 13 loci with cross-population associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE , and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). We additionally identify three population-specific loci with genome-wide significance at/near PTPRK and GRB14 in HIS and KIAA0825 in NHW. Pathway analysis implicates multiple amyloid regulation pathways and the classical complement pathway. Genes at/near our novel loci have known roles in neuronal development ( LRRC4C , LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). Conclusions Using cross-population GWAS meta-analyses, we identify novel LOAD susceptibility loci in/near LRRC4C and LHX5-AS1 , both with known roles in neuronal development, as well as several novel population-unique loci. Reflecting the power of diverse ancestry in GWAS, we detect the SHARPIN locus with only 13.7% of the sample size of the NHW GWAS study ( n  = 409,589) in which this locus was first observed. Continued expansion into larger multi-ancestry studies will provide even more power for further elucidating the genomics of late-onset Alzheimer’s disease.

The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h 2 = 26.3%, 95% CI 23.7–29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10 -8 ) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10 -9 ) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure.

Melatonin regulates circadian rhythms, metabolism, and immunity. Its primary metabolite, 6-sulfatoxymelatonin (aMT6s), is a biomarker linked to cancer risk and metabolic disorders. However, genetic determinants of aMT6s remain poorly understood, with only one prior GWAS limited to an East Asian cohort. We conducted the first multi-ancestry genome-wide association meta-analysis of urinary aMT6s, integrating 11,744 participants from five cohorts: East Asians (Taiwan Biobank), European women (Nurses’ Health Studies), European men (MrOS), and multiethnic participants (MEC). aMT6s was measured from overnight or first-morning urine samples. Association analyses were conducted using both ancestry-aware meta-regression (MR-MEGA) and fixed-effects meta-analysis (METAL). Polygenic risk scores (PRS) were constructed with PRS-CSx and evaluated in phenome-wide analyses in the Mass General Brigham Biobank and UK Biobank. No genome-wide significant loci were identified, and previously reported East Asian signals were not replicated. At suggestive significance, 23 loci emerged, with eight supported by both MR-MEGA and METAL. Several loci showed ancestry-specific heterogeneity, suggesting that genetic associations with urinary aMT6s may vary by population context, although limited power and cohort heterogeneity may also contribute. PRS analyses identified associations with sleep duration and metabolic traits, including type 2 diabetes, but these findings require cautious interpretation. Overall, our results suggest that urinary aMT6s is influenced by a polygenic and potentially population-dependent genetic architecture. This study provides a multi-ancestry framework for investigating melatonin-related biomarkers and highlights the importance of careful interpretation across diverse populations.

Multivariable Mendelian randomization has been largely applied to individuals of European ancestry, due to the larger sample sizes available in European GWAS. We introduce MRBEE-TL, one of the first multi-ancestry multivariable Mendelian randomization methods, which combines transfer learning with bias-corrected estimating equations to improve power in underpowered ancestries and to assess cross-ancestry heterogeneity of disease risk factors. In simulations, MRBEE-TL consistently outperforms MR methods that rely solely on ancestry-specific GWAS data. In real data analyses, MRBEE-TL not only identifies ancestry-consistent and ancestry-specific causal effects missed by conventional methods, but also improves power in underpowered ancestries.