Intraindividual Variability Research Articles

Intrinsic versus extrinsic contribution to intraindividual sweat rate variability of individual eccrine glands

The purpose of the current study was twofold. First, to determine the intraindividual variability of sweat rate per gland for a given skin location during exercise in the heat. Second, to determine the relative importance of intrinsic vs. extrinsic factors as the source of the intraindividual variability in sweat rate per gland. Sweat rate of individual eccrine glands on the forearm was measured following pilocarpine iontophoresis and during exercise in the heat. In five participants during exercise in the heat the measured sweat rate for individual forearm eccrine glands (n = 500) ranged from 0.5 nL/gland/min to 16 nL/gland/min, or over a 30-fold difference. The mean (SD) intraindividual coefficient of variation in sweat rate per gland was 36 (5)% and 49 (10)% (p = 0.008) following pilocarpine iontophoresis and during exercise in the heat, respectively. Such results suggest that intrinsic factors (i.e., sweat gland size and cholinergic sensitivity) contribute approximately three times more than extrinsic factors (i.e., sweat gland nerve fiber density and threshold amplitude) towards explaining the large intra-person variability in sweat rate per gland seen during exercise in the heat.

Early- and Late-Stage Auditory Processing of Speech Versus Non-Speech Sounds in Children With Autism Spectrum Disorder: An ERP and Oscillatory Activity Study.

Individuals with autism spectrum disorder (ASD) often exhibit greater sensitivity to non-speech sounds, reduced sensitivity to speech, and increased variability in cortical activity during auditory speech processing. We assessed differences in cortical responses and variability in early and later processing stages of auditory speech versus non-speech sounds in typically developing (TD) children and children with ASD. Twenty-eight 4- to 9-year-old children (14 ASDs) listened to speech and non-speech sounds during an electroencephalography session. We measured peak amplitudes for early (P2) and later (P3a) stages of auditory processing and inter-trial theta phase coherence as a marker of cortical variability. TD children were more sensitive to speech sounds during early and later processing stages than ASD children, reflected in larger P2 and P3a amplitudes. Individually, twice as many TD children showed reliable differentiation between speech and non-speech sounds compared to children with ASD. Children with ASD showed greater intra-individual variability in theta responses to speech sounds during early and later processing stages. Children with ASD show atypical auditory processing of fundamental speech sounds, perhaps due to reduced and more variable cortical activation. These atypicalities in the consistency of cortical responses to fundamental speech features may impact the development of cortical networks and have downstream effects on more complex forms of language processing.

Cognitive Intra-individual Variability in Cognitively Healthy APOE ε4 Carriers, Mild Cognitive Impairment, and Alzheimer's Disease: a Meta-analysis.

Intra-individual variability (IIV) quantifies an individual's scatter in performances across a test battery (dispersion) or across reaction times within a single task (consistency). No studies have meta-analyzed the cross-sectional IIV literature in those with mild cognitive impairment (MCI) and Alzheimer's dementia (AD). An additional aim of this meta-analysis was to examine IIV in APOE ε4 + healthy control (HC) samples. A systematic search strategy was applied to six databases (Academic Search Complete, PsycINFO, MEDLINE, CINAHL Complete, ERIC, and ProQuest Dissertations & Theses) to identify studies comparing the extent of dispersion- and consistency-based cognitive IIV between clinical (MCI, AD) and HC samples. Thirty-five studies met the inclusion criteria for our random-effects cross-sectional meta-analysis. Hedges' g was used to aggregate between-group effect sizes, with higher positive values indicating clinical > HC IIV. Meta-regression and subgroup-analyses were conducted to evaluate continuous and categorical moderator variables, respectively. Omnibus models yielded analogous moderate-strength, albeit heterogeneous, effects for dispersion and consistency (g = 0.65). Clinical severity was a robust moderator of dispersion (MCI = 0.47, AD = 1.16) and consistency (MCI = 0.51, AD = 1.31) effects. Supplemental analysis of APOE ε4 status in HCs revealed a nonsignificant trend of elevated overall (i.e., dispersion + consistency) IIV in APOE ε4 + vs. APOE ε4 - HC samples (g = 0.24). Cognitive IIV is sensitive to the presence of AD-related genetic risk as well as neurocognitive impairment across the neurocognitive disorder severity spectrum, with a graded-pattern of HC < MCI < AD samples.

Intra-individual variability in lipoprotein(a) among middle-aged population: impact of smoking.

Intra-individual variability in lipoprotein(a) among middle-aged population: impact of smoking.

The Relationship Between Intraindividual Sleep-Wake Variability and Mental Health in Adolescents

ABSTRACT Objective We investigated the relationship between irregular sleep-wake patterns and other aspects of sleep and mental health among adolescents. Methods Community-based sample of adolescents (n = 200, mean age 16.8; 61.7% female) completed baseline assessment (i.e. sleep quality, daytime sleepiness, depressive symptoms, social anhedonia, problematic alcohol use), and 7–8 consecutive days of wearing wrist actigraphy. Irregular sleep-wake patterns were assessed via two methods, both based on actigraphy, to capture day-to-day irregularity (intraindividual variability, IIV) and weekly irregularity (social jet lag, SJL). The Bayesian variability method was performed to calculate IIV in total sleep time (TST), sleep onset, and offset time. SJL was quantified as the actual difference in the sleep midpoint on school days versus non-school days. Results Greater IIV in TST was associated with poorer sleep quality (B = 1.66, 95% CI, 0.14, 3.31, p < .05), and greater depressive symptoms (B = 0.72, 95% CI, 0.17, 1.35, p < .05), while greater IIV in sleep offset time was associated greater depressive symptoms (B = 0.63, 95% CI, 0.03, 1.28, p < .05), and greater problematic alcohol use (B = 0.70, 95% CI, 0.12, 1.35, p < .05), all after adjusting for age, sex, family SES, alcohol drinks, and SJL. No significant association was found with sleep onset time. Greater SJL was associated with poorer sleep quality (B = 0.40, 95% CI, 0.27, 0.54, p < .001) and fewer problematic alcohol uses (B = −0.05, 95% CI, −0.09, −0.00, p < .05), when adjusting for age, sex, family SES, and alcohol drinks. Conclusion Our findings add to a growing body of research on irregularity in sleep-wake patterns and clinical implications.

Exploratory analyses of sleep intraindividual variability and fatigue in parents of children on the autism spectrum.

Fatigue is associated with numerous harmful physical and mental health outcomes. Despite research indicating a relationship between fatigue and sleep, there has been a limited focus on how the variability of a person's sleep may be associated with fatigue. In addition, previous studies have not explicitly explored relationships among child sleep, parent sleep, and parent fatigue. Increasing knowledge about this area of research could be particularly relevant for families with autistic children with an increased likelihood of sleep disturbances. The current study used two weeks of objective sleep (actigraphy) data and subjective ratings of parent fatigue from 81 parents and their autistic children to examine associations among child and parent within-person sleep variability regarding average parent fatigue levels. Evidence was assessed for the role of parent sleep variability in hypothesized connections between child sleep variability and parent fatigue. We found that only greater variability in parents' total sleep time was associated with higher levels of parents' average daily fatigue rating over the two weeks. Child sleep variability was not significantly associated with parent sleep variability or average daily fatigue. In addition, average levels of child sleep were unrelated to parent total sleep time variability and fatigue. Although cautious interpretation is required, findings support the idea that variability in total sleep time may be a unique aspect of parental sleep's association with fatigue, independent of child sleep. In addition, sleep variability could be important to consider when examining sleep in addition to average levels of parameters like total sleep time.

NCOG-24. CHARACTERIZING NEUROTOXICITY ASSOCIATED WITH SYSTEMIC CHEMOTHERAPY IN PATIENTS WITH BREAST CANCER USING DOMAIN-SPECIFIC INTRA-INDIVIDUAL NEUROCOGNITIVE VARIABILITY

Abstract BACKGROUND Systemic chemotherapy is associated with neurotoxicity and neurocognitive functioning (NCF) changes. Intra-individual neurocognitive variability (IIV) is an index of NCF spread/dispersion across neuropsychological tests and can be elevated in patients with breast cancer (BC) after systemic chemotherapy. This study investigated longitudinal IIV changes within NCF domains after chemotherapy to determine whether: (1) IIV for NCF domains are more sensitive to changes than traditional mean-based metrics, and (2) whether changes in domain-specific IIV are associated with changes in mood disturbance or quality of life (QOL). METHODS Prior to and during/shortly after chemotherapy, 37 women with BC were administered a standardized NCF battery including tests within domains of attention/speed of information processing (A/SoP), learning/memory (L/M), and executive functions (EF). Within each domain, the coefficient of variation (CoV) was computed using the standard deviation of normatively-adjusted T-scores while adjusting for intra-individual mean. Patients were assessed for QOL using Functional Assessment of Cancer Therapy-Breast and mood using the STAI and BDI. RESULTS Paired samples t-tests revealed that mean NCF performances declined for L/M (t[36])=-4.44,p&amp;lt;.001,Hedge’s g=.70) and improved for A/SoP (t[36]=3.21,p=.003,g=.29), while CoV increased/worsened for L/M (t[36]=3.82,p&amp;lt;.001,g=.76) but did not change for A/SoP (t[36]=-0.05,p=.959,g=.01). There was no change in EF mean or CoV (ps &amp;gt;.10). No domain mean or IIV change was associated with mood changes (ps&amp;gt;.10). Mean NCF changes were not associated with QOL (ps &amp;gt;.10). Increased/worsened L/M CoV was associated with improved FACT-Breast scale QOL (ρ=.40,p=.020). CONCLUSIONS Both mean- and IIV-based NCF worsened for learning/memory. Discrepancies between mean and IIV change for attention/speed of information processing may be due to differential susceptibility to practice effects. Unexpected associations between learning/memory IIV changes and QOL require further investigation. Future studies are needed to examine NCF dispersion changes across treatment status and in other cancer populations.

Neural bases of social facilitation and inhibition: how peer presence affects elementary eye movements.

Social Facilitation/Inhibition (SFI) refers to how others' presence influences task performance positively or negatively. Our previous study revealed that peer presence modulated saccadic eye movements, a fundamental sensorimotor activity. Pro- and anti-saccades were either facilitated or inhibited depending on trial block complexity (Tricoche et al., 2020). In the present fMRI study, we adapted our paradigm to investigate the neural basis of SFI on saccades. Considering inter- and intra-individual variabilities, we evaluated the shared and distinct neural patterns between social facilitation and inhibition. We predicted an involvement of the saccade-related and attention networks, alongside the Theory-of-Mind (ToM) network, with opposite activity changes between facilitation and inhibition. Results confirmed peer presence modulation in fronto-parietal areas related to saccades and attention, in opposite directions for facilitation and inhibition. Additionally, the ventral attention network was modulated during inhibition. Default mode regions, including ToM areas, were also modulated. Finally, pupil size, often linked to arousal, increased with peers and correlated with dorsal attention regions and anterior insula activities. These results suggest that SFI engages task-specific and domain-general networks, modulated differently based on observed social effect. Attention network seemed to play a central role at both basic (linked to arousal or vigilance) and cognitive control levels.

Shifting GnRH neuron ensembles underlie successive preovulatory luteinizing hormone surges.

The gonadotropin-releasing hormone (GnRH) neurons operate as a neuronal ensemble exhibiting coordinated activity once every reproductive cycle to generate the preovulatory GnRH surge. Using GCaMP fibre photometry at the GnRH neuron distal dendrons to measure the output of this widely scattered population in female mice, we find that the onset, amplitude, and profile of GnRH neuron surge activity exhibits substantial variability from cycle to cycle both between and within individual mice. This was also evident when measuring successive proestrous luteinizing hormone surges. Studies combining short (c-Fos and c-Jun) and long (genetic Robust Activity Marking) term indices of immediate early gene activation revealed that, while ∼50% of GnRH neurons were activated at the time of each surge, only half of these neurons had been active during the previous proestrous surge. These observations reveal marked inter- and intra-individual variability in the GnRH surge mechanism. Remarkably, different sub-populations of overlapping GnRH neurons are recruited to the ensemble each estrous cycle to generate the GnRH surge. While engendering variability in the surge mechanism itself, this likely provides substantial robustness to a key event underlying mammalian reproduction.Significance Statement The mid-cycle luteinizing hormone (LH) surge driven by the gonadotropin-releasing hormone (GnRH) neurons represents the key event triggering ovulation in all mammals. Using GCaMP fibre photometry and genetic activation markers, we unexpectedly find that different sub-populations of GnRH neurons are responsible for driving consecutive LH surges every 4-5 days in cycling female mice. This remarkable oscillatory pattern of network plasticity within the ensemble occurs under normal physiological conditions and likely contributes to the variable timing of the onset of LH surge both within and between individuals. The ability of individual GnRH neurons to take turns within the ensemble in driving the LH surge likely provides a robust fail-safe mechanism for ovulation and contributes to the robustness of mammalian fertility.

Self-reported physical activity and gait in older adults without dementia: A longitudinal study.

Physical activity (PA) is associated with higher gait speed. We aimed to examine the associations between PA and change in spatial and temporal gait measures as well as fall risk in community-dwelling individuals free of dementia. Longitudinal study among 4173 individuals aged ≥50 years (mean age 71 years; 2078 males; median follow-up 4 years) enrolled in the Mayo Clinic Study of Aging. Self-reported late-life PA was used to calculate overall PA and moderate-vigorous PA (MVPA) scores. Gait was assessed using GAITRite® and Zeno™ systems. Incident falls information was based on diagnostic codes retrieved from medical records. We ran linear mixed effects models to examine associations between z-scored PA variables and longitudinal gait parameters, adjusted for age, sex, education, body mass index (BMI), medical comorbidities, and including interactions between PA and time since baseline. In secondary analyses, we calculated Cox Proportional hazard models with age as time scale predicting incident falls by PA, adjusting for sex, education, BMI, medical comorbidities, and falls history. At baseline, higher PA was associated with higher velocity (overall PA: estimate 2.9935; MVPA: 2.2961; p < 0.001), higher cadence (overall PA: 1.0665; MVPA: 0.9073; p < 0.001), greater stride length (overall PA: 2.0805; MVPA: 1.4726; p < 0.001), shorter double support time (overall PA: -0.0257; MVPA: -0.0205; p < 0.001), and lower stance time variability (overall PA: -0.0204, p < 0.001; MVPA: -0.0152; p = 0.006). Overall PA was longitudinally associated with less decline in cadence, and MVPA with less increase in intraindividual stance time variability. Overall PA (Hazard ratio 0.892, 95% confidence interval 0.828-0.961, p = 0.003) and MVPA (HR 0.901; 95% CI 0.835-0.973, p = 0.008) were associated with a decreased risk of incident falls. Late-life PA was associated with favorable gait outcomes and decreased risk of incident falls. Thus, late-life PA may help to maintain gait performance and decrease fall risk in old age.

Understanding Voriconazole Metabolism: A Middle-Out Physiologically-Based Pharmacokinetic Modelling Framework Integrating In Vitro and Clinical Insights.

Voriconazole (VRC), a broad-spectrum antifungal drug, exhibits nonlinear pharmacokinetics (PK) due to saturable metabolic processes, autoinhibition and metabolite-mediated inhibition on their own formation. VRC PK is also characterised by high inter- and intraindividual variability, primarily associated with cytochrome P450 (CYP)2C19 genetic polymorphism. Additionally, recent in vitro findings indicate that VRC main metabolites, voriconazole N-oxide (NO) and hydroxyvoriconazole (OHVRC), inhibit CYP enzymes responsible for VRC metabolism, adding to its PK variability. This variability poses a significant risk of therapeutic failure or adverse events, which are major challenges in VRC therapy. Understanding the underlying processes and sources of these variabilities is essentialfor safe and effective therapy. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) modelling framework that elucidates the complex metabolism of VRC and the impact of its metabolites, NO and OHVRC, on the PK of the parent, leveraging both in vitro and in vivo clinical data in a middle-out approach. A coupled parent-metabolite PBPK model for VRC, NO and OHVRC was developed in a stepwise manner using PK-Sim® and MoBi®. Based on available in vitro data, NO formation was assumed to be mediated by CYP2C19, CYP3A4, and CYP2C9, while OHVRC formation was attributed solely to CYP3A4. Both metabolites were assumed to be excreted via renal clearance, with hepatic elimination also considered for NO. Inhibition functions were implemented to describe the complex interaction network of VRC autoinhibition and metabolite-mediated inhibition on each CYP enzyme. Using a combined bottom-up and middle-out approach, incorporating data from multiple clinical studies and existing literature, the model accurately predicted plasma concentration-time profiles across various intravenous dosing regimens in healthy adults, of different CYP2C19 genotype-predicted phenotypes. All (100%) of the predicted area under the concentration-time curve (AUC) and 94% of maximum concentration (Cmax) values of VRC met the 1.25-fold acceptance criterion, with overall absolute average fold errors of 1.12 and 1.14, respectively. Furthermore, all predicted AUC and Cmax values of NO and OHVRC met the twofold acceptance criterion. This comprehensive parent-metabolite PBPK model of VRC quantitatively elucidated the complex metabolism of the drug and emphasised the substantial impact of the primary metabolites on VRC PK. The comprehensive approachcombining bottom-up and middle-out modelling, therebyaccounting for VRC autoinhibition, metabolite-mediated inhibition, and the impact of CYP2C19 genetic polymorphisms, enhances our understanding of VRC PK. Moreover, the model can be pivotal in designing further in vitro experiments, ultimately allowing for extrapolation to paediatric populations, enhance treatment individualisation and improve clinical outcomes.

Cardioprotective effects of novel antioxidants post-myocardial infarction: An integrative review of preclinical and clinical data

Myocardial infarction (MI), is still a major public health problem, and oxidative stress contributes to the degree of myocardial damage after MI. Oxygen-derived free radicals (ODFR) worsen myocardial injury and result in chronic heart failure in many patients. These harms have led to interest in antioxidant treatment to reduce these adverse effects; new antioxidants with the potential for cardioprotection are the subject of significant interest. This review summarizes basic and clinical research comparing the effectiveness of newly synthesized antioxidants in attenuating oxidative stress and enhancing recovery after myocardial infarction. The review synthesizes evidence of a reduction in infarct size, enhancement of cardiac function, and repression of apoptosis in myocardial cells by the use of antioxidants from animal models. Melatonin, N-acetylcysteine, edaravone, and coenzyme Q10 demonstrated a wide range of preclinical positive effects by acting as ROS free radicals scavengers, modulating mitochondria dysfunction, and reducing inflammation. These findings are extrapolated from humans, although advances in antioxidant therapy are beginning to be viewed in initial clinical trials. From human data, although clinical trials are scarce, the evidence of new antioxidants can improve point and long-term outcomes in patients undergoing MI, help to increase the contractility of the injured myocardium, and decrease the mortality level. However, some issues are still there, such as high inter- and intra-individual variability in patient response and dosing schedule, as well as adverse effects such as pro-oxidant activity at high Oral administered doses of melatonin. The limitations of the current research discussed in this review include the general lack of large-scale, well-controlled clinical trials and the need for long-term follow-up studies. This review also proposed future research directions for improving antioxidant applications in post-MI management.

Metagenomic sequencing of CRISPRs as a new marker to aid in personal identification with low-biomass samples.

The high specificity of the human skin microbiome is expected to provide a new marker for personal identification. Metagenomic sequencing of clustered regularly interspaced short palindromic repeats (CRISPRs), which we call metaCRISPR typing, was shown to achieve personal identification accurately. However, the intra-individual variability observed in previous studies, which may be due to poor DNA yields from skin samples, has resulted in non-reproducible results. Furthermore, whether metaCRISPR typing can assist in the forensic human DNA analysis of low-biomass samples, from which the information obtained is insufficient, is unknown. In the present study, we sequenced serially diluted control streptococcal CRISPRs cloned into plasmids to determine the minimum copy number required to obtain reproducible results from metaCRISPR typing. We found that at least 102 copies of CRISPRs are necessary to obtain reproducible results. We then analyzed the skin swab samples using both metaCRISPR typing and human DNA typing. When the DNA extracted from the skin swabs was diluted, no information was obtained from six out of eight samples by human DNA typing. On the other hand, beta diversity indices of spacer sequences compared with reference samples were below 0.8 for three out of six samples, for which no information was obtained from human DNA analysis, indicating that the spacers observed in these samples were similar to those in the references. These results indicate that metaCRISPR typing may contribute to the identification of individuals from whom the samples were obtained, even in cases where human DNA yields are insufficient to perform human DNA analysis.IMPORTANCEPrevious studies have developed new personal identification methods utilizing personal differences in the skin microbiome. However, intra-individual diversity of skin microbiome may preclude the application of microbiome-based personal identification. Moreover, no study has compared microbiome-based personal identification and practical human DNA analysis. Here, we revealed that the results of metaCRISPR typing, a previously developed microbiome-based personal identification method, are stable if the copy number of the marker gene is sufficient. We then analyzed the skin swab samples using both metaCRISPR typing and human DNA analysis. Our results indicate that metaCRISPR typing may provide additional information for personal identification using low-biomass samples that cannot be used for conventional human DNA analysis.

Neurocognitive Intraindividual Variability in Veterans with Mild Traumatic Brain Injury History and Posttraumatic Stress Disorder.

Veterans with a history of blast-related mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) may be at risk for greater cognitive concerns and worse functional outcomes compared to those with either condition in isolation. However, traditional neuropsychological assessment approaches have yielded equivocal results in these populations. The present study examined an alternative method for detecting subtle cognitive inefficiencies: neurocognitive intraindividual variability (IIV), a measure of within-person performance consistency. Participants were 79 male Veterans with a history of blast-related mTBI and current PTSD (mTBI/PTSD group; n = 54) or neither diagnosis (controls; n = 25). Mean T-scores and IIV scores were calculated from neuropsychological measures of attention and speed of information processing (A/SoP) as well as executive functioning (EF). Global IIV was significantly higher in the mTBI/PTSD group compared to controls (p = .047, Cohen's d = 0.49). At the domain level, larger effect sizes were observed for EF IIV (Cohen's d = 0.46) compared to A/SoP IIV (d = 0.32), although neither were statistically significant. Within the mTBI/PTSD group, higher Global IIV was associated with worse self-reported executive dysfunction, psychological quality of life, and cognitive post-concussive symptoms; at the domain level, these clinical outcomes were generally associated with greater A/SoP IIV (but not EF IIV). Findings extend previous investigations of neurocognitive IIV in individuals with a history of mTBI across PTSD status. Among Veterans with a history of mTBI and comorbid PTSD, neurocognitive variability may be a better indicator of self-reported cognitive inefficiencies and Veteran experience of daily cognitive functioning than mean neuropsychological performances.

Intraindividual variability in lipoprotein(a): the value of a repeat measure for reclassifying individuals at intermediate-risk

Abstract Background Lipoprotein(a) [Lp(a)] is an independent risk factor for cardiovascular disease and outcomes. Levels are predominantly genetically determined and repeat measurements are traditionally considered unlikely to be useful. However, the temporal variation of Lp(a) is not well characterized and it is unclear whether a single measure of Lp(a) is sufficient to assess cardiovascular risk in all individuals. Purpose To determine the intraindividual variability of Lp(a) and whether a repeated measure reclassified Lp(a)-specific cardiovascular risk using the European Atherosclerosis Society (EAS) consensus statement risk categories. Methods This retrospective cohort study analyzed initial and repeated Lp(a) measures obtained using the same laboratory assay from 609 individuals in the Nashville Biosciences database accessed through the American Heart Association Precision Medicine Platform. Categorical variables are presented as counts (%) and compared using Fisher’s exact test. Continuous variables are presented as mean ± standard deviation or median (Q1-Q3), tested for normality using the Shapiro-Wilk test, and compared using parametric and nonparametric tests where appropriate. The Spearman’s Rank correlation coefficient was used to assess the relationship between two variables. The significance level was set at p&amp;lt;0.05. Results Median age was 52.5 (37.1-62.8) years, 45% were women, 80.3% were White patients, 13.3% were Black patients, 1.6% were Asian patients, and 4.8% were other/unknown patients. In terms of relevant comorbidities, 41% had ischemic heart disease, 24.1% had chronic kidney disease, and 13.5% had liver disease. The median time between the two Lp(a) measures was 1.07 (0.5-2.1) years. Our analysis shows a significant difference between the paired Lp(a) values (p&amp;lt;0.05), with 38.1% [95% CI 34.2%-42%] changing by ≥10mg/dL, and 40.5% [95%CI 36.6%-44.3%] changing by &amp;gt;25%. There was a positive correlation between the baseline Lp(a) levels and the absolute changes in Lp(a), (r=0.59, p&amp;lt;0.01). The proportions of individuals with variability are similar in those who were never on the potentially Lp(a)-altering agents (statin, niacin, or PCSK9 inhibitor drugs) (n=91), with 32% [95%CI 22.4%-41.6%] changing by ≥10mg/dL, and 34% [95%CI 24.3%-43.7%] changing by &amp;gt;25%. While over 90% of those whose values were initially in the EAS low-risk and high-risk categories remained in those categories, 53% of those in the intermediate "grey-zone" category transitioned to either the low (20%)- or the high (33%)- risk category (Figure). Conclusion(s) Temporal-related changes in Lp(a) variability were present in many individuals and should be included in calculating the expected effect sizes in future studies targeting Lp(a). A repeat Lp(a) measure may allow more precise Lp(a)-specific cardiovascular risk prediction for individuals whose initial value is in the EAS-defined intermediate "grey-zone" category.

Body weight variability as a predictor of cardiovascular outcomes in type 1 diabetes: A nationwide cohort study.

Intraindividual body weight variability (BWV), that is, the degree of weight fluctuations over time, is associated with an increased risk of cardiovascular diseases (CVDs) in multiple settings. The impact of BWV on cardiovascular risk in type 1 diabetes (T1D) remains unclear, despite the issues relative to weight management in individuals with this condition. Using data from the Swedish National Diabetes Register, we identified individuals with T1D and without CVD at baseline with at least three measurements of body weight taken over three consecutive years. We estimated BWV as quartiles of the standard deviation of weight measures and explored its longitudinal association with the incidence of CVD during a 12.7 ± 4.6 year follow-up through adjusted Cox regression models. The primary endpoint was the composite of nonfatal myocardial infarction, nonfatal stroke and all-cause mortality. We modelled the function of risk in relation to the magnitude of BWV, testing also whether weight trends, that is, increasing, stable or decreasing, age, sex and glycaemic control modified the association between BWV and the outcome. Among the 36 333 individuals with T1D in the register, we identified 19 373 individuals with at least three measures of body weight and without CVD at baseline. Participants with the highest BWV had a 42% increased risk of reaching the primary endpoint compared to those with the lowest BWV (hazard ratio [HR] = 1.42, 95% confidence interval [CI]: 1.24-1.62). In addition, high BWV was significantly associated with a 51% increased risk of all-cause mortality (HR = 1.51, 95% CI: 1.28-1.78), a 37% increased risk of peripheral artery disease (HR = 1.37, 95% CI: 1.06-1.77) and a 55% increased risk of hospitalization for heart failure (HR = 1.55, 95% CI: 1.20-2.01). BWV showed a quasi-linear association with the primary endpoint. No interaction was observed when comparing subgroups for weight trends, sex or degree of glycaemic control. In the subgroup of elderly individuals, the association of BWV with the primary endpoint was no longer significant. High BWV is associated with an increased risk of CVD and all-cause mortality in individuals with T1D, independently of canonical risk factors. Weight trends, sex and glycaemic control do not modify such association while older age attenuates it.

Intra-individual Variability in Lipoprotein(a) Levels: Findings from a Large Academic Health System Population.

Lipoprotein(a) [Lp(a)] levels are known to be mainly genetically determined. However, only scarce data are available on the intra-individual variability of Lp(a) levels across time. We included adult patients (≥18 years old) who had baseline and follow-up Lp(a) measurements (between 1997 and 2024) with a minimum of one year apart. Patients were categorized into three groups as follows: normal (<30 mg/dL), borderline (30 to 50 mg/dL) and high Lp(a) (≥50 mg/dL). Multivariable logistic regression was conducted to assess the predictors of the intra-individual changes in Lp(a) ≥10 mg/dL. A total of 11,669 individuals (median age: 54 years, 60% males) were included in our analysis, with median time between measurements of 4.5 years (IQR: 2.2, 10.6). The median Lp(a) was 16 mg/dL (IQR: 7, 52) at baseline, compared with 15 mg/dL (IQR: 7, 52) at follow-up. At follow-up, 96.4% of individuals with normal Lp(a) and 89.9% with high Lp(a) remained in their categories, while 51.2% with borderline Lp(a) changed their category. Of the included population, 24.9% had an intra-individual Lp(a) change ≥10 mg/dL. Female sex (p <0.001), history of ASCVD (p=0.003), statin therapy (p=0.003) and elevated low-density lipoprotein cholesterol (LDL-C) levels ≥100 mg/dL (p <0.001) were significantly associated with higher odds of intra-individual Lp(a) changes ≥10 mg/dL. Lipoprotein(a) levels were generally stable over time; however, patients with borderline levels may require more than one Lp(a) measurement, especially if they are females, have a history of ASCVD, have elevated LDL-C levels or are on statins therapy.

Comparison of Lower-Limb Muscle Synergies Between Young and Old People During Cycling Based on Electromyography Sensors—A Preliminary Cross-Sectional Study

The purpose of this study was to analyze the lower-limb muscle synergies of young and older adults during stationary cycling across various mechanical conditions to reveal adaptive strategies employed by the elderly to address various common pedaling tasks and function degradation. By comparing lower-limb muscle synergies during stationary cycling between young and old people, this study examined changes in muscle synergy patterns during exercise in older individuals. This is crucial for understanding neuromuscular degeneration and changes in movement patterns in older individuals. Sixteen young and sixteen older experienced cyclists were recruited to perform stationary cycling tasks at two levels of power (60 and 100 W) and three cadences (40, 60, and 90 rpm) in random order. The lower-limb muscle synergies and their inter- and intra-individual variability were analyzed. Three synergies were extracted in this study under all riding conditions in both groups while satisfying overall variance accounted for (VAF) &gt; 85% and muscle VAF &gt; 75%. The older adults exhibited lower variability in synergy vector two and a higher trend in the variability of activation coefficient three, as determined by calculating the variance ratio. Further analyses of muscle synergy structures revealed increased weighting in major contribution muscles, the forward-shifting peak activation in synergy one, and lower peak magnitude in synergy three among older adults. To produce the same cycling power and cadence as younger individuals, older adults make adaptive adjustments in muscle control—increased weighting in major contribution muscles, greater consistency in the use of primary force-producing synergies, and earlier peak activation of subsequent synergy.

Profiles of brain topology for dual-functional stability in old age.

Dual-functional stability (DFS) in cognitive and physical abilities is important for successful aging. This study examines the brain topology profiles that underpin high DFS in older adults by testing two hypotheses: (1) older adults with high DFS would exhibit a unique brain organization that preserves their physical and cognitive functions across various tasks, and (2) any individuals with this distinct brain topology would consistently show high DFS. We analyzed two cohorts of cognitively and physically healthy older adults from the UK (Cam-CAN, n = 79) and the US (CF, n = 48) using neuroimaging data and a combination of cognitive and physical tasks. Variability in DFS was characterized using k-mean clustering for intra-individual variability (IIV) in cognitive and physical tasks. Graph theory analyses of diffusion tensor imaging connectomes were used to assess brain network segregation and integration through clustering coefficients (CCs) and shortest path lengths (PLs). Using support vector machine and regression, brain topology features, derived from PLs + CCs, differentiated the high DFS subgroup from low and mix DFS subgroups with accuracies of 65.82% and 84.78% in Cam-CAN and CF samples, respectively, which predicted cross-task DFS score in CF samples at 58.06% and 70.53% for cognitive and physical stability, respectively. Results showed distinctive neural correlates associated with high DFS, notably varying regional brain segregation and integration within critical areas such as the insula, frontal pole, and temporal pole. The identified brain topology profiles suggest a distinctive neural basis for DFS, a trait indicative of successful aging. These insights offer a foundation for future research to explore targeted interventions that could enhance cognitive and physical resilience in older adults, promoting a healthier and more functional lifespan.

Use of passively collected actigraphy data to detect individual depressive symptoms in a clinical subpopulation and a general population.

The presentation of major depressive disorder (MDD) can vary widely due to its heterogeneity, including inter- and intraindividual symptom variability, making MDD difficult to diagnose with standard measures in clinical settings. Prior work has demonstrated that passively collected actigraphy can be used to detect MDD at a disorder level; however, given the heterogeneous nature of MDD, comprising multiple distinct symptoms, it is important to measure the degree to which various MDD symptoms may be captured by such passive data. The current study investigated whether individual depressive symptoms could be detected from passively collected actigraphy data in a (a) clinical subpopulation (i.e., moderate depressive symptoms or greater) and (b) general population. Using data from the National Health and Nutrition Examination Survey, a large nationally representative sample (N = 8,378), we employed a convolutional neural network to determine which depressive symptoms in each population could be detected by wrist-worn, minute-level actigraphy data. Findings indicated a small-moderate correspondence between the predictions and observed outcomes for mood, psychomotor, and suicide items (area under the receiver operating characteristic curve [AUCs] = 0.58-0.61); a moderate-large correspondence for anhedonia (AUC = 0.64); and a large correspondence for fatigue (AUC = 0.74) in the clinical subpopulation (n = 766); and a small-moderate correspondence for sleep, appetite, psychomotor, and suicide items (AUCs = 0.56-0.60) in the general population (n = 8,378). Thus, individual depressive symptoms can be detected in individuals who likely meet the criteria for MDD, suggesting that wrist-worn actigraphy may be suitable for passively assessing these symptoms, providing important clinical implications for the diagnosis and treatment of MDD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).