👤 Manjinder Sandhu

Individuals with atrial fibrillation (AF) are at increased risk of stroke, cognitive impairment and dementia. Observational studies suggest that anticoagulation may reduce the risk of cognitive decline in patients with AF and elevated thromboembolic risk, implicating subclinical cerebral emboli as a potential mechanistic link. Whether anticoagulation prevents cognitive deterioration in patients with AF at low risk of stroke remains uncertain. Here we conducted a multicenter, double-blind, placebo-controlled trial in which participants with AF and low thromboembolic risk (CHA Show less

Lipoprotein(a) (Lp[a]) can refine atherosclerotic cardiovascular disease risk assessment and guide lipid-lowering therapy intensification (LLTI). However, the association between Lp(a) testing and LLTI across large health systems is not well characterized. Using Veterans Affairs electronic health record data, we conducted a retrospective cohort study of veterans undergoing lipid testing from January 1, 2017, to June 30, 2024. We first compared a 1:1 propensity-matched cohort with concurrent low-density lipoprotein cholesterol (LDL-C) and Lp(a) testing with those with LDL-C testing alone. We then compared veterans with elevated versus nonelevated Lp(a) (>50 versus <50 mg/dL). The primary outcome was LLTI within 12 months, defined as therapy initiation, dose escalation, or addition of another lipid-lowering agent. LDL-C goal attainment (<100 mg/dL primary prevention; <70 mg/dL secondary prevention) was assessed within 12 months. Multivariable logistic regression adjusted for sociodemographic and clinical factors. Among 6 941 840 veterans with LDL-C testing, 10 384 (0.1%) underwent Lp(a) testing. The propensity-matched cohort included 20 768 veterans (mean±SD age, 58.4±15.3 years; 12.4% women; 19.2% Black individuals). Elevated Lp(a) (>50 mg/dL) was present in 25% (n=2562). Lp(a) testing was associated with greater LLTI (odds ratio [OR], 2.11 [95% CI, 1.95-2.29]), LDL-C testing (OR, 1.27 [95% CI, 1.19-1.36]), and LDL-C goal attainment (OR, 1.22 [95% CI, 1.12-1.33]). Compared with Lp(a) <50 mg/dL, Lp(a) >50 mg/dL was associated with increased LLTI (OR, 1.73 [95% CI, 1.55-1.94]). Lp(a) >100 mg/dL was associated with lower LDL-C goal attainment (OR, 0.68 [95% CI, 0.56-0.84]). Lp(a) testing was associated with increased LLTI and LDL-C goal attainment. Elevated Lp(a) identified individuals more likely to undergo LLTI, suggesting testing may motivate preventive treatment optimization. Show less

Lipoprotein(a) [Lp(a)] is underutilized in short-term atherosclerotic cardiovascular disease (ASCVD) risk prediction. This study investigates Lp(a) contribution to short-term ASCVD event prediction using contemporary real-world data and machine learning (ML). A cohort of 731,983 individuals from a claims database was used to investigate the association of Lp(a) with incident ASCVD and all-cause mortality using Cox proportional hazards models. Novel ML models were developed to predict incident ASCVD events at 1, 2, and 3 years after Lp(a) testing. The models were validated in an independent cohort of 53,930 patients. An increase of 50 nmol/L in Lp(a) was independently associated with incident ASCVD events (HR: 1.072; 95% CI: 1.059-1.084) and all-cause mortality (HR: 1.041; 95% CI: 1.015-1.068) after adjustment for age, sex, and race/ethnicity. Novel ML models featuring Lp(a) predicted incident ASCVD events at 1, 2, and 3 years with robust discrimination (C-statistic: 0.83-0.84) in both the derivation and validation cohorts. Modest underestimation of risk was observed in the validation cohort for the 1-year model (calibration slope 1.25). Lp(a) contributed more to 1-year ASCVD prediction than smoking, diabetes, and other lipid parameters. Inclusion of Lp(a) in the 1-year model led to an integrated discrimination improvement of 0.03 and an optimal net reclassification improvement of 10% at a risk threshold of 26%. Lp(a) is a significant predictor of short-term ASCVD risk. Assessing Lp(a) and imminent ASCVD risk may assist in identifying patients who may benefit from escalation of preventative therapies. Show less

Fibroblast growth factor receptors (FGFRs) are a family of cell surface receptors that bind to fibroblast growth factor (FGF) and mediate various cellular functions (translocating proteins, tissue repair, cell proliferation, development, and differentiation) through complex signaling pathways. The FGFR1 growth receptor is essential in the pathogenesis of numerous malignancies, including but not limited to breast cancer, bladder cancer, hepatocellular carcinoma (HCC), and cholangiocarcinoma. The higher levels of FGFR1 expression on the surface of cancer cells cause overly active signaling, which leads to rapid cell proliferation, resulting in a high spread of cancer cells. The kinases that FGFR1 activates migrate across the cell nucleus, activating genes and kinase proteins necessary for the growth and survival of cancerous cells. Therefore, FGFR1 targeting shows therapeutic promise in some diseases, including cancer. Inhibitors of FGFR1s are being developed and studied for their potential to block aberrant FGFR1 signaling and inhibit cancer growth. Since the discovery of new FGFR1 inhibitors in the laboratory is difficult, expensive, time-consuming, and labor-intensive, only a small number of FGFR1 inhibitors have been approved by the FDA for use in the treatment of cancer. To accelerate drug discovery by efficiently exploring the vast chemical space, and identifying potential candidates with higher accuracy and reduced cost, we developed artificial intelligence (AI)-based prediction models for FGFR1 inhibitors using a dataset of 2356 chemical compounds. Four machine learning (ML) algorithms (SVM, RF, k-NN, and ANN) were used to train different prediction models based on molecular descriptors (1D and 2D, with and without molecular fingerprints). Among all trained models, the random forest (RF)-based prediction model achieved the highest accuracy on the training (98.9%), test (89.8%), and external test (90.3%) datasets. The developed inhibitor prediction model (FGFR1Pred) provides a valuable tool for identifying potential FGFR1 inhibitors, expediting the drug discovery process and ultimately facilitating the development of new therapeutics. The model is made available at https://github.com/PGlab-NIPER/FGFR1Pred.git. Show less

The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010-2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of Show less

Oxidative stress (OS) and c-Jun N-terminal kinase (JNK) are both key indicators implicated in neuro-inflammatory signalling pathways and their respective neurodegenerative diseases. Drugs targeting these factors can be considered as suitable candidates for treatment of neuronal dysfunction and memory impairment. The present study encompasses beneficial effects of a naturally occurring triterpenoid, friedelin, against scopolamine-induced oxidative stress and neurodegenerative pathologies in mice models. The treated animals were subjected to behavioural tests i.e., Y-maze and Morris water maze (MWM) for memory dysfunction. The underlying mechanism was determined via western blotting, antioxidant enzymes and lipid profile analyses. Molecular docking studies were carried out to predict the binding modes of friedelin in the binding pocket of p-JNK protein. The results reveal that scopolamine caused oxidative stress by (1) inhibiting catalase (CAT), peroxidase enzyme (POD), superoxide dismutase (SOD), and reduced glutathione enzyme (GSH); (2) the up-regulation of thiobarbituric acid reactive substances (TBARS) in mice brain; and (3) affecting the neuronal synapse (both pre- and post-synapse) followed by associated memory dysfunction. In contrast, friedelin administration not only abolished scopolamine-induced oxidative stress, glial cell activation, and neuro-inflammation but also inhibited p-JNK and NF-κB and their downstream signaling molecules. Moreover, friedelin administration improved neuronal synapse and reversed scopolamine-induced memory impairment accompanied by the inhibition of β-secretase enzyme (BACE-1) to halt amyloidogenic pathways of amyloid-β production. In summary, all of the results show that friedelin is a potent naturally isolated neuro-therapeutic agent to reverse scopolamine-induced neuropathology, which is characteristic of Alzheimer's disease. Show less

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less

Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk. Show less

Whether triglyceride-mediated pathways are causally relevant to coronary heart disease is uncertain. We studied a genetic variant that regulates triglyceride concentration to help judge likelihood of causality. We assessed the -1131T>C (rs662799) promoter polymorphism of the apolipoprotein A5 (APOA5) gene in relation to triglyceride concentration, several other risk factors, and risk of coronary heart disease. We compared disease risk for genetically-raised triglyceride concentration (20,842 patients with coronary heart disease, 35,206 controls) with that recorded for equivalent differences in circulating triglyceride concentration in prospective studies (302 430 participants with no history of cardiovascular disease; 12,785 incident cases of coronary heart disease during 2.79 million person-years at risk). We analysed -1131T>C in 1795 people without a history of cardiovascular disease who had information about lipoprotein concentration and diameter obtained by nuclear magnetic resonance spectroscopy. The minor allele frequency of -1131T>C was 8% (95% CI 7-9). -1131T>C was not significantly associated with several non-lipid risk factors or LDL cholesterol, and it was modestly associated with lower HDL cholesterol (mean difference per C allele 3.5% [95% CI 2.6-4.6]; 0.053 mmol/L [0.039-0.068]), lower apolipoprotein AI (1.3% [0.3-2.3]; 0.023 g/L [0.005-0.041]), and higher apolipoprotein B (3.2% [1.3-5.1]; 0.027 g/L [0.011-0.043]). By contrast, for every C allele inherited, mean triglyceride concentration was 16.0% (95% CI 12.9-18.7), or 0.25 mmol/L (0.20-0.29), higher (p=4.4x10(-24)). The odds ratio for coronary heart disease was 1.18 (95% CI 1.11-1.26; p=2.6x10(-7)) per C allele, which was concordant with the hazard ratio of 1.10 (95% CI 1.08-1.12) per 16% higher triglyceride concentration recorded in prospective studies. -1131T>C was significantly associated with higher VLDL particle concentration (mean difference per C allele 12.2 nmol/L [95% CI 7.7-16.7]; p=9.3x10(-8)) and smaller HDL particle size (0.14 nm [0.08-0.20]; p=7.0x10(-5)), factors that could mediate the effects of triglyceride. These data are consistent with a causal association between triglyceride-mediated pathways and coronary heart disease. British Heart Foundation, UK Medical Research Council, Novartis. Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less

Hereditary multiple exostosis (HME) is an autosomal dominant bone disorder, characterized by short stature and the presence of multiple benign tumors mainly at the ends of long bones. HME is genetically heterogeneous with two known genes on 8q24 (EXT1) and 11p11 (EXT2), and a third minor locus mapped to 19p (EXT3). The majority of EXT1 and EXT2 mutations result in premature protein truncation and loss of function. We analyzed two autosomal dominant HME families of Indian origin. Linkage analysis using fluorescently labeled microsatellite markers at the candidate gene regions was performed. Mutation analysis was carried out by bidirectional sequencing of purified PCR products. We found linkage in one family to EXT1 and in the other family to EXT2. Mutation screening in the EXT1 gene revealed a novel frameshift mutation, a single base deletion in exon 1 (c.142delC). This mutation segregated in all affected members and was absent in the unaffected family members and 60 unrelated controls. In the second family, a previously unreported stop mutation, the substitution c.817C>T, was observed in the EXT2 gene in all affected members and in none of the unaffected family members and 90 unrelated controls. Our findings expand the mutation spectrum of EXT1 and EXT2 and highlight the genetic and phenotypic heterogeneity of HME. Show less

In mouse models, apolipoprotein A-V (apoA-V) exhibits triglyceride (TG)-lowering effects. We investigated the apoA-V/TG relationship and the association of apoA-V with coronary artery disease (CAD) risk by determining serum apoA-V levels and genotypes in a nested case-control (n = 1,034/2,031) study. Both univariate and multivariate apoA-V levels showed no association with future CAD (P = 0.4 and 0.5, respectively). Unexpectedly, there was a significant positive correlation between serum apoA-V and TG in men and women (r = 0.36 and 0.28, respectively, P < 0.001 each) but a negative correlation between apoA-V and LPL mass (r = -0.14 and -0.12 for men and women respectively, P < 0.001 each). The frequency of the c.56C>G polymorphism did not differ between cases and controls despite significant positive association of c.56G with both apoA-V and TG levels. For -1131T>C, the minor allele was significantly associated with lower apoA-V yet higher TG levels and was overrepresented in cases (P = 0.047). The association of -1131T>C with CAD risk, however, was independent of apoA-V levels and likely acts through linkage disequilibrium with APOC3 variants. The positive correlation of apoA-V levels with TG levels, negative correlation with LPL levels, and lack of association with CAD risk highlight the need for further human studies to clarify the role of apoA-V. Show less