CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models

We consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data

Deep phenotyping and genomic data from a nationally representative study on dementia in India

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.Peer reviewe

Correction: CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models.

[This corrects the article DOI: 10.1371/journal.pcbi.1008550.]

CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models.

We consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data

Design and methodology of the harmonized diagnostic assessment of dementia for the longitudinal aging study in India: Wave 2

The rising burden of dementia calls for high-quality data on cognitive decline and dementia onset. The second wave of the Harmonized Diagnostic Assessment for the Longitudinal Aging Study in India (LASI-DAD) was designed to provide longitudinal assessments of cognition and dementia in India. All Wave 1 participants were recruited for a follow-up interview, and a refresher sample was drawn from the Longitudinal Aging Study in India, a nationally representative cohort of Indians aged 45 and older. Respondents underwent a battery of cognitive tests, geriatric assessments, and venous blood collection. Their health and cognitive status were also assessed through an interview with a close family member or friend. Clinical consensus diagnosis was made based on the Clinical Dementia Rating®, and comprehensive data on risk factors of dementia were collected, including neurodegenerative biomarkers, sensory function, and environmental exposures. A total of 4635 participants were recruited between 2022 and 2024 from 22 states and union territories of India, accounting for 97.9% of the population in India. The response rate was 84.0%, and 71.5% of the participants provided venous blood specimen. LASI-DAD provides rich new data to study cognition, dementia, and their risk factors longitudinally in a nationally representative sample of older adults in India. Longitudinal cognitive data, together with longitudinally assessed biomarker data and novel data on sensory function and environmental exposures, provide a unique opportunity to establish associations between risk factors and biologically defined cognitive aging phenotypes

The association of English-Spanish and Indigenous-Spanish bilingualism with cognition among older adults in the Mexican Health and Aging Study (MHAS)

Background While several studies have reported a “bilingual advantage” in cognition among older adults, others have not. Most studies of bilingualism and cognitive aging are in urban settings among high income countries, limiting the generalizability among bilinguals residing in lower-and middle-income countries, such as Mexico. Additionally, the association of bilingualism and cognition among indigenous populations is unknown. In Mexico, there are almost 7 million speakers of indigenous languages, residing primarily in rural areas, and over 15 million people that report speaking English, predominantly in urban settings. To account for sociocultural factors confounding the type of bilingualism (i.e., English-Spanish, Indigenous-Spanish), we evaluated whether bilingualism was associated with better cognitive functioning among adults across urban and rural regions in Mexico. Method Analyses included participants from the Mexican Health and Aging Study (MHAS) aged 55 and older in urban (N = 1053, 12% Spanish-English bilinguals) and rural (N = 814, 20% Spanish-Indigenous bilinguals) areas. Participants reported speaking English and/or an indigenous language in addition to Spanish. Participants completed comprehensive cognitive testing assessing memory, language, executive function, and visuospatial domains. General linear models stratified by region evaluated bilingualism on cognitive domain performance covarying for sociodemographic factors. Result Sociodemographic characteristics differed by region and language group. English-Spanish bilinguals in urban areas were younger, predominantly men, with higher education, less likely illiterate, and with greater U.S. migration history compared to monolinguals. In rural areas, Indigenous-Spanish bilinguals were younger, with less education, higher prevalence of illiteracy, and less likely to have U.S. migration history compared to monolinguals. In urban settings, English-Spanish bilingualism was not associated with performance on any cognitive domain (p\u3e0.05). In rural settings, Indigenous-Spanish bilingualism was associated with worse performance across all cognitive domains (p\u3c0.01). Conclusion There was no evidence of a bilingual cognitive advantage among older adults residing in urban and rural regions in Mexico. While indigenous bilinguals demonstrated the lowest cognitive test performance, further work is required to understand the socioeconomic and environmental factors associated with bilingualism among indigenous populations in Mexico. Greater characterization of their bilingualism (i.e., age and context of acquisition, proficiency, frequency of use) across all languages can help elucidate the association between bilingualism and cognitive test performance

Trajectories and correlates of poor mental health in India over the course of the COVID-19 pandemic: a nationwide survey

Introduction The COVID-19 pandemic had large impacts on mental health; however, most existing evidence is focused on the initial lockdown period and high-income contexts. By assessing trajectories of mental health symptoms in India over 2 years, we aim to understand the effect of later time periods and pandemic characteristics on mental health in a lower-middle income context.Methods We used data from the Real-Time Insights of COVID-19 in India cohort study (N=3709). We used covariate-adjusted linear regression models with generalised estimating equations to assess associations between mental health (Patient Health Questionnaire (PHQ-4) score; range 0–12) and pandemic periods as well as pandemic characteristics (COVID-19 cases and deaths, government stringency, self-reported financial impact, COVID-19 infection in the household) and explored effect modification by age, gender and rural/urban residence.Results Mental health symptoms dropped immediately following the lockdown period but rose again during the delta and omicron waves. Associations between mental health and later pandemic stages were stronger for adults 45 years of age and older (p<0.001). PHQ-4 scores were significantly associated with all pandemic characteristics considered, including estimated COVID-19 deaths (PHQ-4 difference of 0.10 units; 95% CI 0.06 to 0.13), government stringency index (0.14 units; 95% CI 0.11 to 0.18), self-reported major financial impacts (1.20 units; 95% CI 1.09 to 1.32) and COVID-19 infection in the household (0.36 units; 95% CI 0.23 to 0.50).Conclusion While the lockdown period and associated financial stress had the largest mental health impacts on Indian adults, the effects of the pandemic on mental health persisted over time, especially among middle-aged and older adults. Results highlight the importance of investments in mental health supports and services to address the consequences of cyclical waves of infections and disease burden due to COVID-19 or other emerging pandemics

The association of English-Spanish and Indigenous-Spanish bilingualism with cognition among older adults in the Mexican Health and Aging Study (MHAS)

Background While several studies have reported a “bilingual advantage” in cognition among older adults, others have not. Most studies of bilingualism and cognitive aging are in urban settings among high income countries, limiting the generalizability among bilinguals residing in lower-and middle-income countries, such as Mexico. Additionally, the association of bilingualism and cognition among indigenous populations is unknown. In Mexico, there are almost 7 million speakers of indigenous languages, residing primarily in rural areas, and over 15 million people that report speaking English, predominantly in urban settings. To account for sociocultural factors confounding the type of bilingualism (i.e., English-Spanish, Indigenous-Spanish), we evaluated whether bilingualism was associated with better cognitive functioning among adults across urban and rural regions in Mexico. Method Analyses included participants from the Mexican Health and Aging Study (MHAS) aged 55 and older in urban (N = 1053, 12% Spanish-English bilinguals) and rural (N = 814, 20% Spanish-Indigenous bilinguals) areas. Participants reported speaking English and/or an indigenous language in addition to Spanish. Participants completed comprehensive cognitive testing assessing memory, language, executive function, and visuospatial domains. General linear models stratified by region evaluated bilingualism on cognitive domain performance covarying for sociodemographic factors. Result Sociodemographic characteristics differed by region and language group. English-Spanish bilinguals in urban areas were younger, predominantly men, with higher education, less likely illiterate, and with greater U.S. migration history compared to monolinguals. In rural areas, Indigenous-Spanish bilinguals were younger, with less education, higher prevalence of illiteracy, and less likely to have U.S. migration history compared to monolinguals. In urban settings, English-Spanish bilingualism was not associated with performance on any cognitive domain (p\u3e0.05). In rural settings, Indigenous-Spanish bilingualism was associated with worse performance across all cognitive domains (p\u3c0.01). Conclusion There was no evidence of a bilingual cognitive advantage among older adults residing in urban and rural regions in Mexico. While indigenous bilinguals demonstrated the lowest cognitive test performance, further work is required to understand the socioeconomic and environmental factors associated with bilingualism among indigenous populations in Mexico. Greater characterization of their bilingualism (i.e., age and context of acquisition, proficiency, frequency of use) across all languages can help elucidate the association between bilingualism and cognitive test performance

Laparoscopic versus open distal pancreatectomy in the management of traumatic pancreatic disruption

Purpose: Traumatic pancreatic transection is uncommon. The role of laparoscopy in the setting of this injury has not been well described. Patients and Methods: Six large-volume pediatric trauma centers contributed patients \u3c18 years of age who underwent a distal pancreatectomy for traumatic pancreatic transection from 2000 to 2010. Results: Twenty-one patients without another indication for emergency laparotomy underwent a distal pancreatectomy for Grade III pancreatic injuries, of which 7 underwent laparoscopic distal pancreatectomy. Mean (±SD) age was 8.6±4.7 years, and 67% were male. There was no difference in the presence of other injuries between the two groups (43% in each group). Computed tomography revealed a transected pancreas in 85% of the laparoscopic patients and 75% of the open group (P=1.0). Mean operative time was 218±101 minutes with laparoscopy compared with 195±111 minutes with the open procedure (P=.7). Median duration of hospitalization was 6 days (range, 6-18 days) in the laparoscopic group compared with 11 days (range, 5-26 days) in the open group (P=0.3). Postoperative morbidity was not different between the two groups (57% versus 21% for laparoscopic versus open, P=.2). Conclusions: Laparoscopy is equivalent to open distal pancreatectomy in children with select traumatic pancreatic injuries. © Copyright 2012, Mary Ann Liebert, Inc. 2012