Calculating Polygenic Risk Scores (PRS) in UK Biobank: A Practical Guide for Epidemiologists

Association of healthy lifestyle factors and genetic liability with bipolar disorder: Findings from the UK Biobank

BACKGROUND

The interplay between genetic and lifestyle factors in the development of bipolar disorder (BD) remains unclear.

METHODS

A cohort study was carried out on 365,517 participants from the UK Biobank. Lifestyle scores, based on smoking, physical activity, diet, alcohol consumption, sedentary behavior, sleep duration, and social contact, were grouped as favorable (scores 6-7), intermediate (scores 4-5), or unfavorable (scores 0-3). The BD polygenic risk score (PRS) was also categorized into high, intermediate, and low-risk groups using PRS tertiles. Cox regression models determined hazard ratios (HRs) and 95 % confidence intervals (CIs) for BD.

RESULTS

During the 12.9-year follow-up, 529 individuals developed BD. Comparing those with favorable lifestyles to those with unfavorable participants, the HR of developing BD was 3.28 (95 % CI, 2.76-3.89). Similarly, individuals with a high PRS had a risk of 3.20 (95 % CI, 2.83-3.63) compared to those with a low PRS. Notably, individuals with both a high PRS and an unfavorable lifestyle had a significantly higher risk of BD (HR = 6.31, 95 % CI, 4.14-9.63) compared to those with a low PRS and a favorable lifestyle. Additionally, the interaction between PRS and lifestyle contributed an additional risk, with a relative excess risk of 1.74 (95 % CI, 0.40-3.07) and an attributable proportion due to the interaction of 0.37 (95 % CI, 0.16-0.58).

CONCLUSIONS

Our findings suggest that genetic liability for BD, measured as PRS, and lifestyle have an additive effect on the risk of developing BD. A favorable lifestyle was associated with a reduced risk of developing BD.

Pancreatitis polygenic risk score is independently associated with all-cause acute pancreatitis risk in the UK Biobank

BACKGROUND AND AIM

Acute pancreatitis (AP) is a complex disease most commonly caused by gallstones, alcohol intake, or hypertriglyceridemia. Even in subjects with hypertriglyceridemia, the risk of AP is heterogeneous. Identifying individuals with a high genetic susceptibility to AP could contribute to a better risk stratification in the clinic. This study aimed to determine if a weighted polygenic risk score (PRS) of common variants in pancreatitis susceptibility genes can independently predict all-cause AP incidence in the general population.

METHODS

A weighted PRS was calculated for 484 932 individuals from the UK Biobank, including 3346 individuals who developed AP during follow-up. The PRS included eight single nucleotide polymorphisms in known pancreatitis susceptibility genes.

RESULTS

Individuals with a pancreatitis PRS above the 90th percentile had a 1.21-fold (1.03-1.43; P = 0.02) increased risk of AP compared with those with a pancreatitis PRS below the 90th percentile. When comparing individuals in the third tertile versus the first tertile, the risk of AP was 1.13-fold (1.00-1.28; P = 0.06) higher. Individuals with both a high triglyceride (TG) level and a high pancreatitis PRS (third tertile) had a 2.31-fold (1.83-2.93; P = 3.4 × 10-12) increased risk of AP compared with those with a low pancreatitis PRS and a low TG level (first tertile). Overall, the association between pancreatitis PRS and incident AP was independent of baseline TG level.

CONCLUSIONS

Results of this study suggest that the accumulation of common variants in pancreatitis susceptibility genes is associated with all-cause AP incidence. Pancreatitis PRS could help clinicians identify patients who may be at higher risk of AP and who may benefit from more aggressive treatment.

Systemic lupus erythematosus genetics: insights into pathogenesis and implications for therapy

Systemic lupus erythematosus (SLE) is a prime example of how the interplay between genetic and environmental factors can trigger systemic autoimmunity, particularly in young women. Although clinical disease can take years to manifest, risk is established by the unique genetic makeup of an individual. Genome-wide association studies have identified almost 200 SLE-associated risk loci, yet unravelling the functional effect of these loci remains a challenge. New analytic tools have enabled researchers to delve deeper, leveraging DNA sequencing and cell-specific and immune pathway analysis to elucidate the immunopathogenic mechanisms. Both common genetic variants and rare non-synonymous mutations can interact to increase SLE risk. Notably, variants strongly associated with SLE are often located in genome super-enhancers that regulate MHC class II gene expression. Additionally, the 3D conformations of DNA and RNA contribute to genome regulation and innate immune system activation. Improved therapies for SLE are urgently needed and current and future knowledge from genetic and genomic research should provide new tools to facilitate patient diagnosis, enhance the identification of therapeutic targets and optimize testing of agents.

History of Peripartum Depression Moderates the Association Between Estradiol Polygenic Risk Scores and Basal Ganglia Volumes in Major Depressive Disorder

BACKGROUND

The neurobiological differences between women who have experienced a peripartum episode and those who have only had episodes outside of this period are not well understood.

METHODS

64 parous female patients with major depressive disorder that have either a positive (n=30) or negative (n=34) history of peripartum depression (PPD) underwent MRI acquisition to obtain structural brain images. An independent two-sample t-test comparing patients with and without a history of PPD was performed using voxel-based morphometry analysis (VBM). Additionally, polygenic risk scores (PRSs) for estradiol were calculated and a moderation analysis was conducted between 3 estradiol PRSs and PPD history status on extracted cluster volumes using IBM SPSS PROCESS macro.

RESULTS

The VBM analysis identified larger grey matter volumes in bilateral clusters encompassing the putamen, pallidum, caudate, and thalamus in patients with PPD history compared to patients without a history. The moderation analysis identified a significant interaction of 2 estradiol PRSs and PPD history on grey matter cluster volumes with a positive effect in PPD women and a negative effect in women with no history of PPD.

CONCLUSIONS

Our findings demonstrate that women who have experienced a peripartum episode are neurobiologically distinct from women who have no history of PPD in a cluster within the basal ganglia, an area important for motivation, decision-making, and emotional processing. Furthermore, we show that the genetic load for estradiol has a differing effect in this area based on PPD status which supports the claim that PPD is associated with sensitivity to sex steroid hormones.

Gut-Brain Nexus: Mapping Multi-Modal Links to Neurodegeneration at Biobank Scale

Alzheimer's disease (AD) and Parkinson's disease (PD) are influenced by genetic and environmental factors. Using data from UK Biobank, SAIL Biobank, and FinnGen, we conducted an unbiased, population-scale study to: 1) Investigate how 155 endocrine, nutritional, metabolic, and digestive system disorders are associated with AD and PD risk prior to their diagnosis, considering known genetic influences; 2) Assess plasma biomarkers' specificity for AD or PD in individuals with these conditions; 3) Develop a multi-modal classification model integrating genetics, proteomics, and clinical data relevant to conditions affecting the gut-brain axis. Our findings show that certain disorders elevate AD and PD risk before AD and PD diagnosis including: insulin and non-insulin dependent diabetes mellitus, noninfective gastro-enteritis and colitis, functional intestinal disorders, and bacterial intestinal infections, among others. Polygenic risk scores revealed lower genetic predisposition to AD and PD in individuals with co-occurring disorders in the study categories, underscoring the importance of regulating the gut-brain axis to potentially prevent or delay the onset of neurodegenerative diseases. The proteomic profile of AD/PD cases was influenced by comorbid endocrine, nutritional, metabolic, and digestive systems conditions. Importantly, we developed multi-modal prediction models integrating clinical, genetic, proteomic and demographic data, the combination of which performs better than any single paradigm approach in disease classification. This work aims to illuminate the intricate interplay between various physiological factors involved in the gut-brain axis and the development of AD and PD, providing a multifactorial systemic understanding that goes beyond traditional approaches.

Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank

BACKGROUND

Both body mass index (BMI) and genetic factors independently contribute to cardiovascular disease (CVD). However, it is unclear whether genetic risk modifies the association between BMI and the risk of incident CVD. This study aimed to investigate whether BMI categories and genetic risk jointly and interactively contribute to incident CVD events, including hypertension (HTN), atrial fibrillation (AF), coronary heart disease (CHD), stroke, and heart failure (HF).

METHODS

A total of 496,851 participants from the UK Biobank with one or more new-onset CVD events were included in the analyses. BMI was categorized as normal weight (< 25.0 kg/m2), overweight (25.0-29.9 kg/m2), and obesity (≥ 30.0 kg/m2). Genetic risk for each outcome was defined as low (lowest tertile), intermediate (second tertile), and high (highest tertile) using polygenic risk score. The joint associations of BMI categories and genetic risk with incident CVD were investigated using Cox proportional hazard models. Additionally, additive interactions were evaluated.

RESULTS

Among the 496,851 participants, 270,726 (54.5%) were female, with a mean (SD) age was 56.5 (8.1) years. Over a median follow-up (IQR) of 12.4 (11.5-13.1) years, 102,131 (22.9%) participants developed HTN, 26,301 (5.4%) developed AF, 32,222 (6.9%) developed CHD, 10,684 (2.2%) developed stroke, and 13,304 (2.7%) developed HF. Compared with the normal weight with low genetic risk, the obesity with high genetic risk had the highest risk of CVD: HTN (HR: 3.96; 95%CI: 3.84-4.09), AF (HR: 3.60; 95%CI: 3.38-3.83), CHD (HR: 2.76; 95%CI: 2.61-2.91), stroke (HR: 1.44; 95%CI: 1.31-1.57), and HF (HR: 2.47; 95%CI: 2.27-2.69). There were significant additive interactions between BMI categories and genetic risk for HTN, AF, and CHD, with relative excess risk of 0.53 (95%CI: 0.43-0.62), 0.67 (95%CI: 0.51-0.83), and 0.37 (95%CI: 0.25-0.49), respectively.

CONCLUSIONS

BMI and genetic factors jointly and interactively contribute to incident CVD, especially among participants with high genetic risk. These findings have public health implications for identifying populations more likely to have cardiovascular benefit from weight loss interventions.

Breastfeeding in infancy and cardiovascular disease in middle-aged and older adulthood: a prospective study of 0.36 million UK Biobank participants

BACKGROUND

Cardiovascular disease originates in early life. We aimed to investigate the association between breastfeeding in infancy and cardiovascular disease in adult life.

METHODS

We followed 364,240 participants from UK Biobank aged 40-73 years from 2006 - 2010 to 2021. Information on breastfeeding in infancy was self-reported by questionnaire. Cox proportional hazard regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) for the association between breastfeeding and cardiovascular disease in middle-aged and older adulthood. The multivariable Cox models were used by adjusting for the age (used as the time scale), sex, ethnicity, assessment centre, birth weight, multiple birth status, maternal smoking during pregnancy, Townsend deprivation index, smoking status, alcohol drinker status, physical activity, and menopausal status for women. Binary and multinomial multivariable logistic regression models were used to explore the associations of breastfeeding in infancy with cardiovascular disease risk factors including obesity, body composition, metabolic and inflammatory disorders.

RESULTS

During a median of 12.6 years of follow-up, we documented 29,796 new cases of cardiovascular disease, including 24,797 coronary heart disease and 6229 stroke. The multivariable adjusted HRs for breastfed versus non-breastfed were 0.94 (95% CI: 0.91, 0.96) for cardiovascular disease, 0.94 (95% CI: 0.91, 0.96) for coronary heart disease, and 0.95 (95% CI: 0.89, 1.01) for stroke. Furthermore, the strength of observed association between breastfeeding and cardiovascular disease seems to decrease with age (P for interaction <0.001), and increase with polygenic risk for cardiovascular disease (P for interaction <0.001). Consistently, breastfeeding in infancy was associated with cardiovascular disease risk factors including lower body mass index 0.92 (95% CI: 0.89, 0.95), body fat percentage 0.85 (95% CI: 0.83, 0.87), android to gynoid fat ratio 0.89 (95% CI: 0.83, 0.96), visceral adipose tissue 0.92 (95% CI: 0.84, 1.01), as well as lower C-reactive protein level 0.95 (95% CI: 0.94, 0.97) and a lower risk of metabolic syndrome 0.89 (95% CI: 0.85, 0.92).

CONCLUSIONS

Breastfeeding in infancy was associated with a lower risk of cardiovascular disease in middle-aged and older adulthood. Promoting breastfeeding is vital not only for promoting child health, but also for halting the increasing trend of cardiovascular disease in adults.

Polygenic Risk Score (PRS) Combined with NGS Panel Testing Increases Accuracy in Hereditary Breast Cancer Risk Estimation

Breast cancer (BC) is the most prominent tumor type among women, accounting for 32% of newly diagnosed cancer cases. BC risk factors include inherited germline pathogenic gene variants and family history of disease. However, the etiology of the disease remains occult in most cases. Therefore, in the absence of high-risk factors, a polygenic basis has been suggested to contribute to susceptibility. This information is utilized to calculate the Polygenic Risk Score (PRS) which is indicative of BC risk. This study aimed to evaluate retrospectively the clinical usefulness of PRS integration in BC risk calculation, utilizing a group of patients who have already been diagnosed with BC. The study comprised 105 breast cancer patients with hereditary genetic analysis results obtained by NGS. The selection included all testing results: high-risk gene-positive, intermediate/low-risk gene-positive, and negative. PRS results were obtained from an external laboratory (Allelica). PRS-based BC risk was computed both with and without considering additional risk factors, including gene status and family history. A significantly different PRS percentile distribution consistent with higher BC risk was observed in our cohort compared to the general population. Higher PRS-based BC risks were detected in younger patients and in those with FH of cancers. Among patients with a pathogenic germline variant detected, reduced PRS values were observed, while the BC risk was mainly determined by a monogenic etiology. Upon comprehensive analysis encompassing FH, gene status, and PRS, it was determined that 41.90% (44/105) of the patients demonstrated an elevated susceptibility for BC. Moreover, 63.63% of the patients with FH of BC and without an inherited pathogenic genetic variant detected showed increased BC risk by incorporating the PRS result. Our results indicate a major utility of PRS calculation in women with FH in the absence of a monogenic etiology detected by NGS. By combining high-risk strategies, such as inherited disease analysis, with low-risk screening strategies, such as FH and PRS, breast cancer risk stratification can be improved. This would facilitate the development of more effective preventive measures and optimize the allocation of healthcare resources.

Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults

Previous research on autism spectrum disorders (ASD) have showed important volumetric alterations in the cerebellum and brainstem. Most of these studies are however limited to case-control studies with small clinical samples and including mainly children or adolescents. Herein, we aimed to explore the association between the cumulative genetic load (polygenic risk score, PRS) for ASD and volumetric alterations in the cerebellum and brainstem, as well as global brain tissue volumes of the brain among adults at the population level. We utilized the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and constructed the ASD PRS in an independent cohort, the UK Biobank. Regression analyses controlled for multiple comparisons with the false-discovery rate (FDR) at 5% were performed to investigate the association between ASD PRS and forty-four brain magnetic resonance imaging (MRI) phenotypes among ~ 31,000 participants. Primary analyses included sixteen MRI phenotypes: total volumes of the brain, cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), GM of whole cerebellum, brainstem, and ten regions of the cerebellum (I_IV, V, VI, VIIb, VIIIa, VIIIb, IX, X, CrusI and CrusII). Secondary analyses included twenty-eight MRI phenotypes: the sub-regional volumes of cerebellum including the GM of the vermis and both left and right lobules of each cerebellar region. ASD PRS were significantly associated with the volumes of seven brain areas, whereby higher PRS were associated to reduced volumes of the whole brain, WM, brainstem, and cerebellar regions I-IV, IX, and X, and an increased volume of the CSF. Three sub-regional volumes including the left cerebellar lobule I-IV, cerebellar vermes VIIIb, and X were significantly and negatively associated with ASD PRS. The study highlights a substantial connection between susceptibility to ASD, its underlying genetic etiology, and neuroanatomical alterations of the adult brain.

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank

Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.

The polygenic implication of clopidogrel responsiveness: Insights from platelet reactivity analysis and next-generation sequencing

Clopidogrel is widely used worldwide as an antiplatelet therapy in patients with acute coronary disease. Genetic factors influence interindividual variability in response. Some studies have explored the polygenic contributions in the drug response, generating pharmacogenomic risk scores (PgxPRS). Importantly, these factors are less explored in underrepresented populations, such as Latin-American countries. Identifying patients at risk of high-on-treatment platelet reactivity (HTPR) is highly valuable in translational medicine. In this study we used a custom next-generation sequencing (NGS) panel composed of 91 single nucleotide polymorphisms (SNPs) and 28 genes related to clopidogrel metabolism, to analyze 70 patients with platelet reactivity values, assessed through closure time (CT). Our results demonstrated the association of SNPs with HTPR and non-HTPR, revealing the strongest associations with rs2286823 (OR: 5,0; 95% CI: 1,02-24,48; p: 0,03), rs2032582 (OR: 4,41; 95% CI: 1,20-16,12; p: 0,019), and rs1045642 (OR: 3,38; 95% CI: 0,96-11,9; p: 0,05). Bivariate regression analysis demonstrated the significant association of several SNPs with the CT value, a "surrogate" biomarker of clopidogrel response. Exploratory results from the LASSO regression model showed a high discriminatory capacity between HTPR and non-HTPR patients (AUC: 0,955), and the generated PgxPRS demonstrated a significant negative association between the risk score, CT value, and the condition of HTPR and non-HTPR. To our knowledge, our study addresses for the first time the analysis of the polygenic contribution in platelet reactivity using NGS and establishes PgxPRS derived from the LASSO model. Our results demonstrate the polygenic implication of clopidogrel response and offer insights applicable to the translational medicine of antiplatelet therapy in an understudied population.

Effects of polygenic risk score and sodium and potassium intake on hypertension in Asians: A nationwide prospective cohort study

Genetic factors, lifestyle, and diet have been shown to play important roles in the development of hypertension. Increased salt intake is an important risk factor for hypertension. However, research on the involvement of genetic factors in the relationship between salt intake and hypertension in Asians is lacking. We aimed to investigate the risk of hypertension in relation to sodium and potassium intake and the effects of genetic factors on their interactions. We used Korean Genome and Epidemiology Study data and calculated the polygenic risk score (PRS) for the effect of systolic and diastolic blood pressure (SBP and DBP). We also conducted multivariable logistic modeling to evaluate associations among incident hypertension, PRSSBP, PRSDBP, and sodium and potassium intake. In total, 41,351 subjects were included in the test set. The top 10% PRSSBP group was the youngest of the three groups (bottom 10%, middle, top 10%), had the highest proportion of women, and had the highest body mass index, baseline BP, red meat intake, and alcohol consumption. The multivariable logistic regression model revealed the risk of hypertension was significantly associated with higher PRSSBP, higher sodium intake, and lower potassium intake. There was significant interaction between sodium intake and PRSSBP for incident hypertension especially in sodium intake ≥2.0 g/day and PRSSBP top 10% group (OR 1.27 (1.07-1.51), P = 0.007). Among patients at a high risk of incident hypertension due to sodium intake, lifestyle modifications and sodium restriction were especially important to prevent hypertension.

Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers

Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.

Polygenic Risk Scores and the Risk of Childhood Overweight/Obesity in Association With the Consumption of Sweetened Beverages: A Population-Based Cohort Study

Background: Sugar-sweetened beverage (SSB) and non-nutritive sweetened beverage (NNSB) consumption is associated with obesity and are targets for population-level dietary interventions. In children (<16 years), we evaluate whether SSB or NNSB consumption is associated with subsequent (2 years later) overweight and/or obesity, and the effect of consumption on subsequent overweight/obesity differs by BMI polygenic risk score (BMI-PRS). Methods: The nationally representative Longitudinal-Study-of-Australian-Children had biennial data collection from birth (n = 5107) until age 14/15 years (n = 3127). At age 11/12 years, a comprehensive biomedical assessment, including PRS assessment, was undertaken (n = 1422). Parent- or self-reported beverage consumption (SSBs: soft drinks, energy drinks, and/or juice; NNSBs: diet drinks) was measured as any/none over previous 24 hours. BMI-PRS was derived using published results (high PRS ≥75th percentile). At ages 4/5-14/15 children were classified as having obesity, overweight/obesity, or not having overweight/obesity using BMI z-score (CDC cut points). Results: SSB consumption had limited association with subsequent overweight/obesity. NNSB consumption was associated with ∼8% more children with subsequent overweight/obesity at most ages. In older children with high BMI-PRS, associations between NNSB consumption and subsequent overweight/obesity strengthened with age [at age 14-15 for high BMI-PRS, difference in proportion with overweight/obesity among NNSB consumers vs. nonconsumers = 0.38 (95% confidence interval: 0.22 to 0.55, p ≤ 0.001)]. There was limited association between SSB consumption and BMI-PRS. Conclusion: NNSB consumption was associated with increased risk of overweight/obesity for children with greater genetic risk at older ages (12-15 years). Focused intervention among children with high genetic risk could target NNSB consumption; however, reverse causality (children with genetic risk and/or high BMI consume more NNSBs) cannot be excluded.

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn's Disease

BACKGROUND

The lack of reliable biomarkers in response to anti-TNFα biologicals hinders personalized therapy for Crohn's disease (CD) patients. The motivation behind our study is to shift the paradigm of anti-TNFα biomarker discovery toward specific immune cell sub-populations using single-cell RNA sequencing and an innovative approach designed to uncover PBMCs gene expression signals, which may be masked due to the treatment or ongoing inflammation; Methods: The single-cell RNA sequencing was performed on PBMC samples from CD patients either naïve to biological therapy, in remission while on adalimumab, or while on ustekinumab but previously non-responsive to adalimumab. Sieves for stringent downstream gene selection consisted of gene ontology and independent cohort genomic profiling. Replication and meta-analyses were performed using publicly available raw RNA sequencing files of sorted immune cells and an association analysis summary. Machine learning, Mendelian randomization, and oligogenic risk score methods were deployed to validate DEGs highly relevant to anti-TNFα therapy response; Results: This study found PLCB1 in CD4+ T cells and CRTAM in double-negative T cells, which met the stringent statistical thresholds throughout the analyses. An additional assessment proved causal inference of both genes in response to anti-TNFα therapy; Conclusions: This study, jointly with an innovative design, uncovered novel candidate genes in the anti-TNFα response landscape of CD, potentially obscured by therapy or inflammation.

Clinical biomarker-based biological aging and risk of benign prostatic hyperplasia: A large prospective cohort study

Objective

Chronological age (CAge), biological age (BAge), and accelerated age (AAge) are all important for aging-related diseases. CAge is a known risk factor for benign prostatic hyperplasia (BPH); However, the evidence of association of BAge and AAge with BPH is limited. This study aimed to evaluate the association of CAge, Bage, and AAge with BPH in a large prospective cohort.

Method

A total of 135,933 males without BPH at enrolment were extracted from the UK biobank. We calculated three BAge measures (Klemera-Doubal method, KDM; PhenoAge; homeostatic dysregulation, HD) based on 16 biomarkers. Additionally, we calculated KDM-BAge and PhenoAge-BAge measures based on the Levine method. The KDM-AAge and PhenoAge-AAge were assessed by the difference between CAge and BAge and were standardized (mean = 0 and standard deviation [SD] = 1). Cox proportional hazard models were applied to assess the associations of CAge, Bage, and AAge with incident BPH risk.

Results

During a median follow-up of 13.150 years, 11,811 (8.690%) incident BPH were identified. Advanced CAge and BAge measures were associated with an increased risk of BPH, showing threshold effects at a later age (all P for nonlinearity <0.001). Nonlinear relationships between AAge measures and risk of BPH were also found for KDM-AAge (P = 0.041) and PhenoAge-AAge (P = 0.020). Compared to the balance comparison group (-1 SD < AAge < 1 SD), the accelerated aging group (AAge > 2 SD) had a significantly elevated BPH risk with hazard ratio (HR) of 1.115 (95% CI, 1.000-1.223) for KDM-AAge and 1.180 (95% CI, 1.068-1.303) for PhenoAge-AAge, respectively. For PhenoAge-AAge, subgroup analysis of the accelerated aging group showed an increased HR of 1.904 (95% CI, 1.374-2.639) in males with CAge <50 years and 1.233 (95% CI, 1.088-1.397) in those having testosterone levels <12 nmol/L. Moreover, AAge-associated risk of BPH was independent of and additive to genetic risk.

Conclusions

Biological aging is an independent and modifiable risk factor for BPH. We suggest performing active health interventions to slow biological aging, which will help mitigate the progression of prostate aging and further reduce the burden of BPH.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese

BACKGROUND

Given the high prevalence of BPH among elderly men, pinpointing those at elevated risk can aid in early intervention and effective management. This study aimed to explore that polygenic risk score (PRS) is effective in predicting benign prostatic hyperplasia (BPH) incidence, prognosis and risk of operation in Han Chinese.

METHODS

A retrospective cohort study included 12,474 male participants (6,237 with BPH and 6,237 non-BPH controls) from the Taiwan Precision Medicine Initiative (TPMI). Genotyping was performed using the Affymetrix Genome-Wide TWB 2.0 SNP Array. PRS was calculated using PGS001865, comprising 1,712 single nucleotide polymorphisms. Logistic regression models assessed the association between PRS and BPH incidence, adjusting for age and prostate-specific antigen (PSA) levels. The study also examined the relationship between PSA, prostate volume, and response to 5-α-reductase inhibitor (5ARI) treatment, as well as the association between PRS and the risk of TURP.

RESULTS

Individuals in the highest PRS quartile (Q4) had a significantly higher risk of BPH compared to the lowest quartile (Q1) (OR = 1.51, 95% CI = 1.274-1.783, p < 0.0001), after adjusting for PSA level. The Q4 group exhibited larger prostate volumes and a smaller volume reduction after 5ARI treatment. The Q1 group had a lower cumulative TURP probability at 3, 5, and 10 years compared to the Q4 group. PRS Q4 was an independent risk factor for TURP.

CONCLUSIONS

In this Han Chinese cohort, higher PRS was associated with an increased susceptibility to BPH, larger prostate volumes, poorer response to 5ARI treatment, and a higher risk of TURP. Larger prospective studies with longer follow-up are warranted to further validate these findings.

Pancreatitis polygenic risk score is associated with acute pancreatitis in multifactorial chylomicronemia syndrome

BACKGROUND

Multifactorial chylomicronemia syndrome (MCS) is a severe form of hypertriglyceridemia associated with an increased risk of acute pancreatitis (AP). The risk of AP is heterogenous and is associated with increased level of triglycerides (TG) and presence of rare variants in TG metabolism-related genes.

OBJECTIVE

To determine if the accumulation of common variants in pancreatitis susceptibility genes, measured with a weighted polygenic risk score (PRS), is associated with AP in MCS patients.

METHODS

A total of 114 patients with MCS underwent genetic testing for eight single nucleotide polymorphisms (SNPs) in known pancreatitis susceptibility genes (ABCG8, CLDN2, CTRB1/2, CTRC, PRSS1, PRSS2, SPINK1 and TWIST2). A weighted PRS was calculated to account for the phenotypic effect of each SNP locus.

RESULTS

A high pancreatitis-PRS score (≥ 0.44) was associated with a 2.94-fold increase risk of AP (p = 0.02) among patients with MCS. MCS patients with a high pancreatitis-PRS and a rare variant in TG metabolism-related gene have a 9.50-fold increase risk of AP (p = 0.001), compared to those with a low-PRS and no rare variant. A multivariate analysis including the presence of rare variants, the maximal TG values and a high pancreatitis-PRS explained 26% of the variability in AP in MCS patients.

CONCLUSION

This study shows for the first time that the accumulation of common variants in pancreatitis susceptibility genes is associated with AP in MCS patients. Pancreatitis-PRS could help clinicians to identify MCS patients who may be at higher risk of AP and who may benefit from more aggressive treatment.

Genetic susceptibility to schizophrenia through neuroinflammatory pathways is associated with retinal thinning: Findings from the UK-Biobank

The human retina is part of the central nervous system and can be easily and non-invasively imaged with optical coherence tomography. While imaging the retina may provide insights on central nervous system-related disorders such as schizophrenia, a typical challenge are confounders often present in schizophrenia which may negatively impact retinal health. Here, we therefore aimed to investigate retinal changes in the context of common genetic variations conveying a risk of schizophrenia as measured by polygenic risk scores. We used population data from the UK Biobank, including White British and Irish individuals without diagnosed schizophrenia, and estimated a polygenic risk score for schizophrenia based on the newest genome-wide association study (PGC release 2022). We hypothesized that greater genetic susceptibility to schizophrenia is associated with retinal thinning, especially within the macula. To gain additional mechanistic insights, we conducted pathway-specific polygenic risk score associations analyses, focusing on gene pathways that are related to schizophrenia. Of 65484 individuals recruited, 48208 participants with available matching imaging-genetic data were included in the analysis of whom 22427 (53.48%) were female and 25781 (46.52%) were male. Our robust principal component regression results showed that polygenic risk scores for schizophrenia were associated with retinal thinning while controlling for confounding factors (b = -0.03, p = 0.007, pFWER = 0.01). Similarly, we found that polygenic risk for schizophrenia specific to neuroinflammation gene sets revealed significant associations with retinal thinning (b = -0.03, self-contained p = 0.041 (reflecting the level of association), competitive p = 0.05 (reflecting the level of enrichment)). These results go beyond previous studies suggesting a relationship between manifested schizophrenia and retinal phenotypes. They indicate that the retina is a mirror reflecting the genetic complexities of schizophrenia and that alterations observed in the retina of individuals with schizophrenia may be connected to an inherent genetic predisposition to neurodegenerative aspects of the condition. These associations also suggest the potential involvement of the neuroinflammatory pathway, with indications of genetic overlap with specific retinal phenotypes. The findings further indicate that this gene pathway in individuals with a high polygenic risk for schizophrenia could contribute through acute-phase proteins to structural changes in the retina.

Association of Blood Pressure With Brain Ages: A Cohort Study of Gray and White Matter Aging Discrepancy in Mid-to-Older Adults From UK Biobank

BACKGROUND

Gray matter (GM) and white matter (WM) impairments are both associated with raised blood pressure (BP), although whether elevated BP is differentially associated with the GM and WM aging process remains inadequately examined.

METHODS

We included 37 327 participants with diffusion-weighted imaging (DWI) and 39 630 participants with T1-weighted scans from UK Biobank. BP was classified into 4 categories: normal BP, high-normal BP, grade 1, and grade 2 hypertension. Brain age gaps (BAGs) for GM (BAGGM) and WM (BAGWM) were derived from diffusion-weighted imaging and T1 scans separately using 3-dimensional-convolutional neural network deep learning techniques.

RESULTS

There was an increase in both BAGGM and BAGWM with raised BP (P<0.05). BAGWM was significantly larger than BAGGM at high-normal BP (0.195 years older; P=0.006), grade 1 hypertension (0.174 years older; P=0.004), and grade 2 hypertension (0.510 years older; P<0.001), but not for normal BP. Mediation analysis revealed that the association between hypertension and cognitive decline was primarily mediated by WM impairment. Mendelian randomization analysis suggested a causal relationship between hypertension and WM aging acceleration (unstandardized B, 1.780; P=0.016) but not for GM (P>0.05). Sliding-window analysis indicated the association between hypertension and brain aging acceleration was moderated by chronological age, showing stronger correlations in midlife but weaker associations in the older age.

CONCLUSIONS

Compared with GM, WM was more vulnerable to raised BP. Our study provided compelling evidence that concerted efforts should be directed towards WM damage in individuals with hypertension in clinical practice.

Polygenic Risk Scores for Glaucoma Onset in the Ocular Hypertension Treatment Study

Importance

Primary open-angle glaucoma (POAG) is a highly heritable disease, with 127 identified risk loci to date. Polygenic risk score (PRS) may provide a clinically useful measure of aggregate genetic burden and improve patient risk stratification.

Objective

To assess whether a PRS improves prediction of POAG onset in patients with ocular hypertension.

Design, Setting, and Participants

This was a post hoc analysis of the Ocular Hypertension Treatment Study. Data were collected from 22 US sites with a mean (SD) follow-up of 14.0 (6.9) years. A total of 1636 participants were followed up from February 1994 to December 2008; 1077 participants were enrolled in an ancillary genetics study, of which 1009 met criteria for this analysis. PRS was calculated using summary statistics from the largest cross-ancestry POAG meta-analysis, with weights trained using 8 813 496 variants from 449 186 cross-ancestry participants in the UK Biobank. Data were analyzed from July 2022 to December 2023.

Exposures

From February 1994 to June 2002, participants were randomized to either topical intraocular pressure-lowering medication or close observation. After June 2002, both groups received medication.

Main Outcomes and Measures

Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent areas under the receiver operating characteristic curve were used to compare the predictive performance of multivariable Cox proportional hazards models.

Results

Of 1009 included participants, 562 (55.7%) were female, and the mean (SD) age was 55.9 (9.3) years. The mean (SD) PRS was significantly higher for 350 POAG converters (0.24 [0.95]) compared with 659 nonconverters (-0.12 [1.00]) (P < .001). POAG risk increased 1.36% (95% CI, 1.08-1.64) with each higher PRS decile, with conversion ranging from 9.52% (95% CI, 7.09-11.95) in the lowest PRS decile to 21.81% (95% CI, 19.37-24.25) in the highest decile. Comparison of low-risk and high-risk PRS tertiles showed a 2.0-fold increase in 20-year POAG risk for participants of European and African ancestries. In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year (95% CI, 0.01-1.03) decrease in age at diagnosis (P = .047). No significant linear association between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C index = 0.77) compared with the Ocular Hypertension Treatment Study baseline model (C index = 0.75) (P < .001). Each 1-SD higher PRS conferred a mean hazard ratio of 1.25 (95% CI, 1.13-1.44) for POAG onset.

Conclusions and Relevance

Higher PRS was associated with increased risk for POAG in patients with ocular hypertension. The inclusion of a PRS improved the prediction of POAG onset.

Trial Registration

ClinicalTrials.gov Identifier: NCT00000125.

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

Plasma protein signatures of adult asthma

BACKGROUND

Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma.

METHODS

Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)).

RESULTS

Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis.

CONCLUSION

This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.

Long-term ambient ozone, omega-3 fatty acid, genetic susceptibility, and risk of mental disorders among middle-aged and older adults in UK biobank

BACKGROUND

Evidence linking ozone to depression and anxiety disorders remains sparse and results are heterogeneous. It remains unknown whether omega-3 fatty acid, or genetic susceptibility of mental disorders modify the impacts of ozone. The aim is to assess the associations of ambient ozone with depression and anxiety, and further explore the potential modification effects of omega-3 fatty acid and genetic susceptibility.

METHODS

In total of 257,534 participants were enrolled from 2006 to 2010 and followed up to 2016. Depression and anxiety were assessed using mental health questionnaires, primary care records and hospital admission records. The annual average concentrations of ozone were calculated and linked to individuals by home address. Dietary intake and plasma concentration were selected to reflect levels of omega-3 fatty acid. Polygenetic risk scores were selected to reflect genetic susceptibility. We examined the associations of ozone and incident mental disorders, and potential modification of omega-3 fatty acid and genetic susceptibility.

RESULTS

Incidences of depression (N = 6957) and anxiety (N = 6944) was associated with increase of ozone. Higher levels of omega-3 fatty acid might attenuate the ozone related depression risk. However, the modification effects of genetic susceptibility were not found.

CONCLUSIONS

Long-term exposure to ambient ozone increase the risk of mental disorders among the middle aged and older adults, and omega-3 fatty acid could reduce the adverse effects of ozone on mental health. Higher intake of omega-3 fatty acid is a potential strategy to prevent the risks caused by ozone on public mental health.

Polygenic Risk Score in Predicting Esophageal, Oropharyngeal, and Hypopharynx Cancer Risk among Taiwanese Population

Esophageal cancer shares strong associations with oropharyngeal and hypopharyngeal cancers, primarily due to shared risk factors like excessive tobacco and alcohol use. This retrospective study at Taichung Veterans General Hospital involved 54,692 participants, including 385 with squamous cell carcinoma (SCC) of the esophagus, oropharynx, or hypopharynx. Using a polygenic risk score (PRS) derived from 8353 single-nucleotide polymorphisms, researchers aimed to assess its correlation with cancer incidence and prognosis. The study found a 1.83-fold higher risk of esophageal, oropharyngeal, and hypopharyngeal SCCs in participants with a high PRS (Q4) compared to the low-PRS group (Q1). Esophageal cancer risk demonstrated a significant positive association with the PRS, as did hypopharyngeal cancer. Clinical parameters and staging showed limited associations with PRS quartiles, and the PRS did not significantly impact recurrence or mortality rates. The research highlighted that a higher PRS is linked to increased susceptibility to esophageal and hypopharyngeal cancer. Notably, a specific polygenic risk score, PGS001087, exhibited a discernible association with SCC risk, particularly in specific subtypes and advanced disease stages. However, it was not significantly linked to clinical cancer staging, emphasizing the multifactorial nature of cancer development. This hospital study reveals that a higher PRS correlates with increased susceptibility to esophageal and hypopharyngeal cancers. Notably, PGS001087 shows a discernible association with SCC risk in specific subtypes and advanced stages, although not significantly linked to clinical cancer staging. These findings enhance our understanding of genetic factors in upper aerodigestive tract cancers, particularly esophageal SCC, guiding future research and risk assessment strategies.

The sulfur microbial diet and risk of nonalcoholic fatty liver disease: a prospective gene-diet study from the UK Biobank

BACKGROUND

The gut microbiota is closely related to liver diseases. The dietary pattern associated with sulfur-metabolizing bacteria in stool has been found to influence intestinal health.

OBJECTIVE

We aimed to investigate whether consuming the sulfur microbial diet is associated with nonalcoholic fatty liver disease (NAFLD).

METHODS

We included 143,918 participants of European descent from the UK Biobank. Information on serving sizes used per diet component was recorded by an online 24-h dietary assessment tool (Oxford WebQ). The total sulfur microbial diet score was constructed by summing the product of β-coefficients and corresponding serving sizes. NAFLD was ascertained using hospital inpatient and death records. Cox proportional hazard models were used to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI). Mediation analyses were used to investigate underlying mediators including body mass index, waist circumference, glucose, triglyceride, urate, and C-reactive protein. A polygenic risk score for NAFLD was constructed and stratified to assess whether the association is modified by genetic predisposition.

RESULTS

After a median follow-up of 11.7 y (interquartile range: 11.3-12.5 y), we documented 1540 incident cases of NAFLD. After adjustment for covariates, we observed an overall J-shaped relationship between the sulfur microbial diet and risk of NAFLD. Those in the highest quartile of sulfur microbial diet score had a 46% increased risk of NAFLD [HRQ4vsQ1 (95% CI): 1.46 (1.26, 1.69)]. We also found that this association is partly mediated by metabolic disorders and systemic inflammation. In addition, the positive association was stronger among individuals at higher genetic risk for NAFLD (Pinteraction = 0.044).

CONCLUSIONS

The sulfur microbial diet had adverse associations with incident NAFLD, particularly in those at a higher genetic risk. Our study may provide evidence on the role of sulfur-metabolizing bacteria in the diet-NAFLD association.

Mismatch negativity and polygenic risk scores for schizophrenia and bipolar disorder

OBJECTIVE

Auditory mismatch negativity (MMN) impairment is a candidate endophenotype in psychotic disorders, yet the genetic underpinnings remain to be clarified. Here, we examined the relationships between auditory MMN and polygenic risk scores (PRS) for individuals with psychotic disorders, including schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) and in healthy controls (HC).

METHODS

Genotyped and clinically well-characterized individuals with psychotic disorders (n = 102), including SSD (n = 43) and BD (n = 59), and HC (n = 397) underwent a roving MMN paradigm. In addition MMN, we measured the memory traces of the repetition positivity (RP) and the deviant negativity (DN), which is believed to reflect prediction encoding and prediction error signals, respectively. SCZ and BD PRS were computed using summary statistics from the latest genome-wide association studies. The relationships between the MMN, RP, and DN and the PRSs were assessed with linear regressions.

RESULTS

We found no significant association between the SCZ or BD PRS and grand average MMN in the psychotic disorders group or in the HCs group (all p > 0.05). SCZ PRS and BD PRS were negatively associated with RP in the psychotic disorders group (β = -0.46, t = -2.86, p = 0.005 and β = -0.29, t = -0.21, p = 0.034, respectively). No significant associations were found between DN and PRS.

CONCLUSION

These findings suggest that genetic variants associated with SCZ and BD may be associated with MMN subcomponents linked to predictive coding among patients with psychotic disorders. Larger studies are needed to confirm these findings and further elucidate the genetic underpinnings of MMN impairment in psychotic disorders.

Evaluating the Efficacy of Type 2 Diabetes Polygenic Risk Scores in an Independent European Population

Numerous type 2 diabetes (T2D) polygenic risk scores (PGSs) have been developed to predict individuals' predisposition to the disease. An independent assessment and verification of the best-performing PGS are warranted to allow for a rapid application of developed models. To date, only 3% of T2D PGSs have been evaluated. In this study, we assessed all (n = 102) presently published T2D PGSs in an independent cohort of 3718 individuals, which has not been included in the construction or fine-tuning of any T2D PGS so far. We further chose the best-performing PGS, assessed its performance across major population principal component analysis (PCA) clusters, and compared it with newly developed population-specific T2D PGS. Our findings revealed that 88% of the published PGSs were significantly associated with T2D; however, their performance was lower than what had been previously reported. We found a positive association of PGS improvement over the years (p-value = 8.01 × 10-4 with PGS002771 currently showing the best discriminatory power (area under the receiver operating characteristic (AUROC) = 0.669) and PGS003443 exhibiting the strongest association PGS003443 (odds ratio (OR) = 1.899). Further investigation revealed no difference in PGS performance across major population PCA clusters and when compared with newly developed population-specific PGS. Our findings revealed a positive trend in T2D PGS performance, consistently identifying high-T2D-risk individuals in an independent European population.

Polygenic risk score model for renal cell carcinoma in the Korean population and relationship with lifestyle-associated factors

BACKGROUND

The polygenic risk score (PRS) is used to predict the risk of developing common complex diseases or cancers using genetic markers. Although PRS is used in clinical practice to predict breast cancer risk, it is more accurate for Europeans than for non-Europeans because of the sample size of training genome-wide association studies (GWAS). To address this disparity, we constructed a PRS model for predicting the risk of renal cell carcinoma (RCC) in the Korean population.

RESULTS

Using GWAS analysis, we identified 43 Korean-specific variants and calculated the PRS. Subsequent to plotting receiver operating characteristic (ROC) curves, we selected the 31 best-performing variants to construct an optimal PRS model. The resultant PRS model with 31 variants demonstrated a prediction rate of 77.4%. The pathway analysis indicated that the identified non-coding variants are involved in regulating the expression of genes related to cancer initiation and progression. Notably, favorable lifestyle habits, such as avoiding tobacco and alcohol, mitigated the risk of RCC across PRS strata expressing genetic risk.

CONCLUSION

A Korean-specific PRS model was established to predict the risk of RCC in the underrepresented Korean population. Our findings suggest that lifestyle-associated factors influencing RCC risk are associated with acquired risk factors indirectly through epigenetic modification, even among individuals in the higher PRS category.

Multi-ancestry genome-wide meta-analysis identifies novel basal cell carcinoma loci and shared genetic effects with squamous cell carcinoma

Basal cell carcinoma (BCC) is one of the most common malignancies worldwide, yet its genetic determinants are incompletely defined. We perform a European ancestry genome-wide association (GWA) meta-analysis and a Hispanic/Latino ancestry GWA meta-analysis and meta-analyze both in a multi-ancestry GWAS meta-analysis of BCC, totaling 50,531 BCC cases and 762,234 controls from four cohorts (GERA, Mass-General Brigham Biobank, UK Biobank, and 23andMe research cohort). Here we identify 122 BCC-associated loci, of which 36 were novel, and subsequently fine-mapped these associations. We also identify an association of the well-known pigment gene SLC45A2 as well as associations at RCC2 and CLPTM1L with BCC in Hispanic/Latinos. We examine these BCC loci for association with cutaneous squamous cell carcinoma (cSCC) in 16,407 SCC cases and 762,486 controls of European ancestry, and 33 SNPs show evidence of association. Our study findings provide important insights into the genetic basis of BCC and cSCC susceptibility.

The accuracy of polygenic score models for anthropometric traits and Type II Diabetes in the Native Hawaiian Population

Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations, and their accuracies have not been evaluated for Native Hawaiians. Using body mass index, height, and type-2 diabetes as examples of highly polygenic traits, we evaluated the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5,300 individuals. We evaluated both publicly available PGS models or genome-wide PGS models trained in this study using the largest available GWAS. We found evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also found that using the Native Hawaiian samples as an optimization cohort during training did not consistently improve PGS performance. Moreover, even the best performing PGS models among Native Hawaiians would have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.

Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.

Association of Kallikrein Related Peptidase 3 (KLK3) gene with dermatophytosis in the UK biobank cohort

BACKGROUND

In a previous genome wide association study (GWAS) of UK Biobank (UKB) data, we identified one susceptibility locus, tubulointerstitial nephritis antigen (TINAG), with genome wide significance for dermatophytosis. We used genotype calls from file UKB22418. These data are derived directly from Affymetrix DNA microarrays but are missing many genotype calls. Using computationally efficient approaches, UKB has entered imputed genotypes into a second dataset, UKB22828, increasing the number of testable variants by over 100-fold to 96 million variants.

METHODS

In the current study, we used UKB imputed genotypes in UKB22828 to identify dermatophytosis susceptibility loci. To identify cases of dermatophytosis, we used ICD10 code B35, which covers tinea barbae, tinea capitis, tinea unguium, tinea manuum, tinea pedis, tinea corporis, tinea imbricata, tinea cruris, other dermatophytoses and dermatophytosis, unspecified. We used PLINK, a whole-genome association analysis toolset, to analyse the UKB22828 chromosome files.

RESULTS

GWAS summary (Manhattan) plot of the meta-analysis association statistics highlighted two susceptibility loci, TINAG and Kallikrein Related Peptidase 3 (KLK3), with genome wide significance for dermatophytosis. KLK3, also known as prostate specific antigen (PSA), belongs to a subclass of serine proteases with a variety of physiological functions.

CONCLUSION

KLK3 may be a dermatophytosis susceptibility gene. KLK3 could affect risk of dermatophytosis, since kallikreins are necessary for normal homeostasis of the skin.

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.

Genetic factors, adherence to healthy lifestyle behaviors, and risk of bladder cancer

BACKGROUND

Genetic and lifestyle factors both contribute to the pathogenesis of bladder cancer, but the extent to which the increased genetic risk can be mitigated by adhering to a healthy lifestyle remains unclear. We aimed to investigate the association of combined lifestyle factors with bladder cancer risk within genetic risk groups.

METHODS

We conducted a prospective study of 375 998 unrelated participants of European ancestry with genotype and lifestyle data and free of cancer from the UK biobank. We generated a polygenic risk score (PRS) using 16 single nucleotide polymorphisms and a healthy lifestyle score based on body weight, smoking status, physical activity, and diet. Cox models were fitted to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of genetic and lifestyle factors on bladder cancer.

RESULTS

During a median follow-up of 11.8 years, 880 participants developed bladder cancer. Compared with those with low PRS, participants with intermediate and high PRS had a higher risk of bladder cancer (HR 1.29, 95% CI 1.07-1.56; HR 1.63, 95% CI 1.32-2.02, respectively). An optimal lifestyle was associated with an approximately 50% lower risk of bladder cancer than a poor lifestyle across all genetic strata. Participants with a high genetic risk and a poor lifestyle had 3.6-fold elevated risk of bladder cancer compared with those with a low genetic risk and an optimal lifestyle (HR 3.63, 95% CI 2.23 -5.91).

CONCLUSIONS

Adhering to a healthy lifestyle could substantially reduce the bladder cancer risk across all genetic strata, even for high-genetic risk individuals. For all populations, adopting an intermediate lifestyle is more beneficial than a poor one, and adhering to an optimal lifestyle is the ideal effective strategy for bladder cancer prevention.

PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data

Motivation

Currently, the Polygenic Score (PGS) Catalog curates over 400 publications on over 500 traits corresponding to over 3000 polygenic risk scores (PRSs). To assess the feasibility of privately calculating the underlying multivariate relative risk for individuals with consumer genomics data, we developed an in-browserPRS calculator for genomic data that does not circulate any data or engage in any computation outside of the user's personal device.

Results

A prototype personal risk score calculator, created for research purposes, was developed to demonstrate how the PGS Catalog can be privately and readily applied to readily available direct-to-consumer genetic testing services, such as 23andMe. No software download, installation, or configuration is needed. The PRS web calculator matches individual PGS catalog entries with an individual's 23andMe genome data composed of 600k to 1.4 M single-nucleotide polymorphisms (SNPs). Beta coefficients provide researchers with a convenient assessment of risk associated with matched SNPs. This in-browser application was tested in a variety of personal devices, including smartphones, establishing the feasibility of privately calculating personal risk scores with up to a few thousand reference genetic variations and from the full 23andMe SNP data file (compressed or not).

Availability and implementation

The PRScalc web application is developed in JavaScript, HTML, and CSS and is available at GitHub repository (https://episphere.github.io/prs) under an MIT license. The datasets were derived from sources in the public domain: [PGS Catalog, Personal Genome Project].

Risk Prediction of Chronic Rhinosinusitis with or without Nasal Polyps in Taiwanese Population Using Polygenic Risk Score for Nasal Polyps

The association between single nucleotide polymorphisms and chronic rhinosinusitis (CRS) has been determined. However, it was not known whether the polygenic risk score (PRS) for nasal polyps (NP) could predict CRS with NP (CRSwNP) or without NP (CRSsNP). The aim of this study was to investigate the association between PRSs for NP and the risk of CRS with or without NP. Data from 535 individuals with CRS and 5350 control subjects in the Taiwan Precision Medicine Initiative project were collected. Four PRSs for NP, including PGS000933, PGS000934, PGS001848, and PGS002060 from UK Biobank, were tested in these participants. They were divided into four groups according to quartiles of PRSs. The logistic regression model was performed to evaluate CRSwNP and CRSsNP risk according to PRSs for NP. The PGS002060 had the highest area under the curve at 0.534 for CRSsNP prediction and at 0.588 for CRSwNP prediction. Compared to subjects in the lowest PRS category, the PGS002060 significantly increased the odds for CRSsNP by 1.48 at the highest quintile (p = 0.003) and by 2.32 at the highest quintile for CRSwNP (p = 0.002). In addition, the odds for CRSwNP increased by 3.01 times in female CRSwNP patients (p = 0.009) at the highest quintile compared with those in the lowest PRS category. The PRSs for NP developed from European populations could be applied to the Taiwanese population to predict CRS risk, especially for female CRSwNP.

Well-being spectrum traits are associated with polygenic scores for autism

Individuals with autism spectrum disorder (ASD) tend to experience lower well-being as demonstrated mostly for children and adolescents in epidemiological studies. A further investigation of inclusive well-being, in terms of five well-being spectrum (5-WBS) traits including neuroticism, depression, loneliness, life satisfaction, and positive affect, among adults with ASD may deepen our understanding of their well-being, and lead to the possibility to further modify societal supportive mechanisms for individuals with ASD. This study aims to investigate if a genetic predisposition for ASD is associated with 5-WBS traits using polygenic risk score (PRS) analysis. PRS for ASD were calculated based on the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and were created in the independent cohort UK Biobank. Regression analyses were performed to investigate the association between ASD PRS and 5-WBS traits in the UK Biobank population including 337,423 individuals. ASD PRS were significantly associated with all 5-WBS traits, showing a positive association with the negative WBS traits, neuroticism (max R2  = 0.04%, p < 1 × 10-4 ), depression (max R2  = 0.06%, p < 1 × 10-4 ), loneliness (max R2  = 0.04%, p < 1 × 10-4 ), and a negative association with the positive WBS traits, life satisfaction (max R2  = 0.08%, p < 1 × 10-4 ), positive affect (max R2  = 0.10%, p < 1 × 10-4 ). The findings suggest that adults carrying a high load of risk single nucleotide peptides (SNPs) for ASD are more likely to report decreased well-being. The study demonstrates a considerable connection between susceptibility to ASD, its underlying genetic etiology and well-being.

Genetic propensity for cerebral amyloidosis and risk of mild cognitive impairment and Alzheimer's disease within a cognitive reserve framework

INTRODUCTION

We constructed a polygenic risk score (PRS) for β-amyloid (PRSAβ42) to proxy AD pathology and investigated its association with incident Alzheimer's disease (AD)/amnestic mild cognitive impairment (aMCI) and the influence of cognitive reserve (CR), proxied by educational years, on the relationship between PRSAβ42 and AD/aMCI risk.

METHODS

A total of 618 cognitive-normal participants were followed-up for 2.92 years. The association of PRSAβ42 and CR with AD/aMCI incidence was examined with COX models. Then we examined the additive interaction between PRSAβ42 and CR and the CR effect across participants with different PRSAβ42 levels.

RESULTS

Higher PRSAβ42 and CR were associated with a 33.9% higher risk and 8.3% less risk for AD/aMCI, respectively. An additive interaction between PRSAβ42 and CR was observed. High CR was associated with 62.6% less risk of AD/aMCI incidence only in the high-PRSAβ42 group.

DISCUSSION

A super-additive effect of PRSAβ42 and CR on AD/aMCI risk was observed. CR influence was evident in participants with high PRSAβ42.

TMEM132D and VIPR2 Polymorphisms as Genetic Risk Loci for Retinal Detachment: A Genome-Wide Association Study and Polygenic Risk Score Analysis

Purpose

Retinal detachment (RD) is a sight-threatening ocular disease caused by separation of the neurosensory retina from the underlying retinal pigment epithelium layer. Its genetic basis is unclear because of a limited amount of data. In this study, we aimed to identify genetic risk loci associated with RD in participants without diabetes mellitus and to construct a polygenic risk score (PRS) to predict the risk of RD.

Methods

A genome-wide association study was conducted using data from the Taiwan Biobank to identify RD risk loci. A total of 1533 RD cases and 106,270 controls were recruited, all of whom were Han Chinese. Replication studies were performed using data from the UK Biobank and Biobank Japan. To construct the PRS, a traditional clumping and thresholding method was performed and validated by fivefold cross-validation.

Results

Two novel loci with significant associations were identified. These two genes were TMEM132D (lead single nucleotide polymorphism [SNP]: rs264498, adjusted-P = 7.18 × 10-9) and VIPR2 (lead SNP: rs3812305, adjusted-P = 8.38 × 10-9). The developed PRS was effective in discriminating individuals at high risk of RD with a dose-response relationship. The quartile with the highest risk had an odds ratio of 1244.748 compared to the lowest risk group (95% confidence interval, 175.174-8844.892).

Conclusions

TMEM132D and VIPR2 polymorphisms are genetic candidates linked to RD in Han Chinese populations. Our proposed PRS was effective at discriminating high-risk from low-risk individuals.

Polygenic Risk Score Improves Prediction of Primary Open Angle Glaucoma Onset in the Ocular Hypertension Treatment Study

Objective or Purpose

Primary open-angle glaucoma (POAG) is a highly heritable disease with 127 identified risk loci. Polygenic risks score (PRS) offers a measure of aggregate genetic burden. In this study, we assess whether PRS improves risk stratification in patients with ocular hypertension.

Design

A post-hoc analysis of the Ocular Hypertension Treatment Study (OHTS) data.

Setting Participants and/or Controls

1636 participants were followed from 1994 to 2020 across 22 sites. The PRS was computed for 1009 OHTS participants using summary statistics from largest cross-ancestry POAG metanalysis with weights trained using 8,813,496 variants from 488,395 participants in the UK Biobank.

Methods Interventions or Testing

Survival regression analysis, with endpoint as development of POAG, predicted disease onset from PRS incorporating baseline covariates.

Main Outcomes and Measures

Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent AUC were used to compare the predictive performance of multivariable Cox-Proportional Hazards models.

Results

Mean PRS was significantly higher for POAG-converters (0.24 ± 0.95) than for non-converters (-0.12 ± 1.00) (p < 0.01). POAG risk increased 1.36% with each higher PRS decile, with conversion ranging from 9.5% in the lowest PRS decile to 21.8% in the highest decile. Comparison of low- and high-risk PRS tertiles showed a 1.8-fold increase in 20-year POAG risk for participants of European and African ancestries (p<0.01). In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year decrease in age at diagnosis, (p=0.05). No significant linear relationship between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C-index = 0.77) compared to OHTS baseline model (C-index=0.75) (p<0.01). One standard deviation higher PRS conferred a mean hazard ratio of 1.25 (CI=[1.13, 1.44]) for POAG onset.

Conclusions

Higher PRS is associated with increased risk for, and earlier development of POAG in patients with ocular hypertension. Early treatment may mitigate the risk from high genetic burden, delaying clinically detectable disease by up to 5.2 years. The inclusion of a PRS improves the prediction of POAG onset.

Identification of Novel Intronic SNPs in Transporter Genes Associated with Metformin Side Effects

Metformin is a widely used and effective medication in type 2 diabetes (T2DM) as well as in polycystic ovary syndrome (PCOS). Single nucleotide polymorphisms (SNPs) contribute to the occurrence of metformin side effects. The aim of the present study was to identify intronic genetic variants modifying the occurrence of metformin side effects and to replicate them in individuals with T2DM and in women with PCOS. We performed Next Generation Sequencing (Illumina Next Seq) of 115 SNPs in a discovery cohort of 120 metformin users and conducted a systematic literature review. Selected SNPs were analysed in two independent cohorts of individuals with either T2DM or PCOS, using 5'-3'exonucleaseassay. A total of 14 SNPs in the organic cation transporters (OCTs) showed associations with side effects in an unadjusted binary logistic regression model, with eight SNPs remaining significantly associated after appropriate adjustment in the discovery cohort. Five SNPs were confirmed in a combined analysis of both replication cohorts but showed different association patterns in subgroup analyses. In an unweighted polygenic risk score (PRS), the risk for metformin side effects increased with the number of risk alleles. Intronic SNPs in the OCT cluster contribute to the development of metformin side effects in individuals with T2DM and in women with PCOS and are therefore of interest for personalized therapy options.

Association between night shift work and NAFLD: a prospective analysis of 281,280 UK Biobank participants

CONTEXT

This study aimed to investigate the association between night shift work and the risk of nonalcoholic fatty liver disease (NAFLD).

METHODS

We conducted a prospective analysis of 281,280 UK Biobank participants. Cox proportional hazards models were used to estimate the association of night shift work with incident NAFLD. Polygenic risk score analyses were performed to assess whether a genetic predisposition to NAFLD modified the association.

RESULTS

During a median follow-up of 12.1 years (3,373,964 person-years), 2,555 incident NAFLD cases were identified. Compared with workers who never/rarely worked night shifts, those who worked some night shifts or usual/permanent night shifts were 1.12 (95% CI: 0.96-1.31) and 1.27 (95% CI: 1.08-1.48) times more likely to develop NAFLD, respectively. Among the 75,059 participants who had reports on lifetime experience of night shift work, those with a longer duration, a higher frequency, more consecutive night shifts and a longer length per shift all showed higher risks of incident NAFLD. Further analyses showed that the association between night shift work and incident NAFLD was not modified by a genetic predisposition to NAFLD.

CONCLUSIONS

Night shift work was associated with increased risks of incident NAFLD.

Biomarkers selection and mathematical modeling in biological age estimation

Biological age (BA) is important for clinical monitoring and preventing aging-related disorders and disabilities. Clinical and/or cellular biomarkers are measured and integrated in years using mathematical models to display an individual's BA. To date, there is not yet a single or set of biomarker(s) and technique(s) that is validated as providing the BA that reflects the best real aging status of individuals. Herein, a comprehensive overview of aging biomarkers is provided and the potential of genetic variations as proxy indicators of the aging state is highlighted. A comprehensive overview of BA estimation methods is also provided as well as a discussion of their performances, advantages, limitations, and potential approaches to overcome these limitations.

Evaluation of polygenic risk score for risk prediction of gastric cancer

Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated.

Robust SNP-based prediction of rheumatoid arthritis through machine-learning-optimized polygenic risk score

BACKGROUND

The popular statistics-based Genome-wide association studies (GWAS) have provided deep insights into the field of complex disorder genetics. However, its clinical applicability to predict disease/trait outcomes remains unclear as statistical models are not designed to make predictions. This study employs statistics-free machine-learning (ML)-optimized polygenic risk score (PRS) to complement existing GWAS and bring the prediction of disease/trait outcomes closer to clinical application. Rheumatoid Arthritis (RA) was selected as a model disease to demonstrate the robustness of ML in disease prediction as RA is a prevalent chronic inflammatory joint disease with high mortality rates, affecting adults at the economic prime. Early identification of at-risk individuals may facilitate measures to mitigate the effects of the disease.

METHODS

This study employs a robust ML feature selection algorithm to identify single nucleotide polymorphisms (SNPs) that can predict RA from a set of training data comprising RA patients and population control samples. Thereafter, selected SNPs were evaluated for their predictive performances across 3 independent, unseen test datasets. The selected SNPs were subsequently used to generate PRS which was also evaluated for its predictive capacity as a sole feature.

RESULTS

Through robust ML feature selection, 9 SNPs were found to be the minimum number of features for excellent predictive performance (AUC > 0.9) in 3 independent, unseen test datasets. PRS based on these 9 SNPs was significantly associated with (P < 1 × 10^-16) and predictive (AUC > 0.9) of RA in the 3 unseen datasets. A RA ML-PRS calculator of these 9 SNPs was developed ( https://xistance.shinyapps.io/prs-ra/ ) to facilitate individualized clinical applicability. The majority of the predictive SNPs are protective, reside in non-coding regions, and are either predicted to be potentially functional SNPs (pfSNPs) or in high linkage disequilibrium (r2 > 0.8) with un-interrogated pfSNPs.

CONCLUSIONS

These findings highlight the promise of this ML strategy to identify useful genetic features that can robustly predict disease and amenable to translation for clinical application.

Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis

Osteoporosis (OP) is a multifactorial bone disease belonging to the metabolic osteopathies group. Using the polygenic score (PGS) approach, we combined the effects of bone mineral density (BMD) DNA loci, affecting osteoporosis pathogenesis, based on GEFOS/GENOMOS consortium GWAS meta-analysis. We developed models to predict the risk of low fractures in women from the Volga-Ural region of Russia with efficacy of 74% (AUC = 0.740; OR (95% CI) = 2.9 (2.353–3.536)), as well as the formation of low BMD with efficacy of 79% (AUC = 0.790; OR (95% CI) = 3.94 (2.993–5.337)). In addition, we propose a model that predicts fracture risk and low BMD in a comorbid condition with 85% accuracy (AUC = 0.850; OR (95% CI) = 6.6 (4.411–10.608)) in postmenopausal women.