SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations

Опубликована: Окт. 17, 2024

Polygenic risk scores are widely used in disease stratification, but their accuracy varies across diverse populations. Recent methods large-scale leverage multi-ancestry data to improve under-represented populations require labelling individuals by ancestry for prediction. This poses challenges practical use, as clinical practices typically not based on ancestry. We propose SPLENDID, a novel penalized regression framework biobank-scale data. Our method utilizes principal component interactions model genetic continuum within single prediction all ancestries, eliminating the need discrete labels. In extensive simulations and analyses of 9 traits from All Us Research Program (N=224,364) UK Biobank (N=340,140), SPLENDID significantly outperformed existing sparsity. By directly incorporating continuous training, stands valuable tool robust fairer implementation.

Язык: Английский

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Methylation Clocks Do Not Predict Age or Alzheimer's Disease Risk Across Genetically Admixed Individuals

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 18, 2024

Abstract Epigenetic clocks that quantify rates of aging from DNA methylation patterns across the genome have emerged as a potential biomarker for risk age-related diseases, like Alzheimer’s disease (AD), and environmental social stressors. However, not been validated in genetically diverse cohorts. Here we evaluate set 621 AD patients matched controls African American, Hispanic, white co-horts. The are less accurate at predicting age admixed individuals, especially those with substantial ancestry, than cohort. also do consistently identify acceleration cases compared to controls. Methylation QTL (meQTL) commonly influence CpGs clocks, these meQTL significantly higher frequencies genetic ancestries. Our results demonstrate often fail predict beyond their training populations suggest avenues improving portability.

Язык: Английский

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Evaluating metabolome-wide causal effects on risk for psychiatric and neurodegenerative disorders

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 7, 2024

Abstract Evidence indicates phenotypic and biological overlap between psychiatric neurodegenerative disorders. Further identification of underlying mutual unique mechanisms may yield novel multi-disorder disorder-specific therapeutic targets. The metabolome represents an important domain for target as metabolites play critical roles in modulating a diverse range processes. Here, we used Mendelian randomisation (MR) to test the causal effects ∼1000 plasma ∼300 metabolite ratios on anxiety, bipolar disorder, depression, schizophrenia, amyotrophic lateral sclerosis, Alzheimer’s disease, Parkinson’s disease multiple sclerosis. In total, 85 involving 77 passed FDR correction robust sensitivity analyses (IVW-MR OR range: 0.73-1.48; p < 0.05). No evidence reverse causality was identified. Multivariate implicated sphingolipid metabolism disorder risk carnitine derivatives sclerosis However, polygenic scores prioritised showed limited prediction UK Biobank. Downstream colocalisation regions containing influential variants identified greater than suggestive (PP.H4 ≥ 0.6) shared variant 29 metabolite/psychiatric trait-pairs chromosome 11 at FADS gene cluster. Most these were lipids linoleic or arachidonic acid. Additional ratio histidine-to-glutamine, glutamine, SPRYD4 expression 12. Although no single had effect results suggest broad across brain Metabolites here help inform future targeted interventions.

Язык: Английский

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Lipid Trajectories Improve Risk Models for Alzheimer’s Disease and Mild Cognitive Impairment

Journal of Lipid Research, Год журнала: 2024, Номер unknown, С. 100714 - 100714

Опубликована: Ноя. 1, 2024

In this retrospective, case-control study, we tested the hypothesis that blood-lipid concentrations during decade prior to cognitive symptom onset can inform risk prediction for Alzheimer's disease (AD) and stable mild impairment (MCI). Clinically well-characterized cases were diagnosed using DSM-IV criteria; MCI had been ≥5 years; controls propensity matched at (MCI: 116 cases, 435 controls; AD: 215 483 controls). Participants grouped based on (i) longitudinal trajectories (ii) quintile of variability independent mean (VIM) total cholesterol (TC), high-density lipoprotein (HDL-C), low-density cholesterol, non-HDL-C, ln(triglycerides). Risk models evaluated contributions lipid trajectory VIM groups relative APOE genotype or polygenic scores (PRS) AD levels major confounders: age, lipid-lowering medications, comorbidities, other correlates concentrations. with AD-PRS, higher MCI-risk was associated two lower HDL-C [odds ratios: 3.8(1.3-11.3; P=0.014), 3.2(1.1-9.3; P=0.038), high trajectory], lowest non-HDL-C ratio: 2.2 (1.3-3.8:P=0.004), quintiles 2-5]. Higher AD-risk 2.8(1.5-5.1; P=0.001), 3.7 (2.0-7.0; P<0.001)], TC 2.5(1.5-4.0: P<0.001)]. Inclusion lipid-trajectory improved risk-model predictive performance lipid-level PRS. These results provide important real-world perspectives how variation contribute decline.

Язык: Английский

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