Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features.

paper Primary Public

Authors: Kamarajan, Chella; Pandey, Ashwini K; Chorlian, David B; Meyers, Jacquelyn L; Kinreich, Sivan; Pandey, Gayathri; Subbie-Saenz de Viteri, Stacey; Zhang, Jian; Kuang, Weipeng; Barr, Peter B; Aliev, Fazil; Anokhin, Andrey P; Plawecki, Martin H; Kuperman, Samuel; Almasy, Laura; Merikangas, Alison; Brislin, Sarah J; Bauer, Lance; Hesselbrock, Victor; Chan, Grace; Kramer, John; Lai, Dongbing; Hartz, Sarah; Bierut, Laura J; McCutcheon, Vivia V; Bucholz, Kathleen K; Dick, Danielle M; Schuckit, Marc A; Edenberg, Howard J; Porjesz, Bernice
Year: 2023
Journal: Behavioral sciences (Basel, Switzerland)
PMID: 37232664
DOI: 10.3390/bs13050427
PMCID: PMC10215235

Figure 1

The multi-way importance plot showing the top significant variables (labeled and marked with black circles) that contributed to the differentiation of the memory group from the control subjects based on the measures Gini decrease, number of trees, and p-value. Features related to alcohol-related clinical/health outcomes stood top in the importance list, followed by functional connectivity, personality, and PRS measures. Note that the variables that were not significant (purple dots) are not highlighted. (See footnote of Table 5 for the list of abbreviations for the measures shown here.)

Figure 2

Panels (A–E): Significant default mode network connections within each frequency band, which contributed to the random forest distinction of the memory group from control individuals. The blue and brown beads represent ROIs of the left and right hemisphere, respectively, while the blue and brown lines represent hypoconnectivity and hyperconnectivity, respectively, in the memory group. Panel (F): Significant hippocampal connections that contributed to the memory vs. control classification. Seven of the eight hippocampal connections showed hyperconnectivity in the memory group. Note that all hypoconnected networks involved an anterior cingulate node. Refer to Figure S2 in the Supplementary Materials for the ROI locations and anatomical views/axes.

Figure 3

Correlation matrix showing associations among the top significant variables. Values of the cells in red/pink shades represent negative r-values, and those in blue/cyan shades indicate positive r-values between variables that correspond to the vertical and horizontal axes. A darker color represents a higher magnitude of r-values. Significant correlations (before Bonferroni correction) are marked with asterisks in black font (* p < 0.05; ** p < 0.01; and *** p < 0.001), and those that survived Bonferroni correction are marked with a triple plus sign (+++) in white font. For the abbreviations in the variable labels, see the footnote of Table 5.

#	Section	Preview
0	1. Introduction	Alcohol use disorder (AUD) is a chronic, relapsing disorder [1,2] with a range of neurocognitive…
1	1. Introduction	Brain oscillations representing electrical signals of neural activity, as recorded by the…
2	1. Introduction	Recent studies have used source localization methods, such as exact low-resolution brain…
3	1. Introduction	AUD is a multi-factorial disorder; therefore, it is important for the predictive models of…
4	1. Introduction	questionnaires, and (iv) measures of alcohol consumption and associated health consequences from the…
5	2. Materials and Methods — 2.1. Sample	The sample for the present study was drawn from a recent follow-up assessment study [44,45] of…
6	2. Materials and Methods — 2.1. Sample	may not be readily generalizable to other populations. Nonetheless, datasets enriched for specific…
7	2. Materials and Methods — 2.2. Recent Telephone Interview	The recent follow-up telephone interview (10–20 min) was designed to collect information regarding…
8	2. Materials and Methods — 2.3. EEG Data Acquisition and Preprocessing	Details of assessments and EEG recording in COGA, which is identical at all sites, can be found in…
9	2. Materials and Methods — 2.4. EEG Functional Connectivity Analysis Using eLORETA	EEG functional connectivity was computed using the eLORETA software [22,55], a validated tool for…
10	2. Materials and Methods — 2.5. Functional Connectivity across the Default Mode Network	The default mode network regions analyzed in the study are the posterior cingulate cortex (PCC), the…
11	2. Materials and Methods — 2.6. Assessment of Temperament, Personality, and Alcohol Experience	The temperament, personality, and life experience data included scores from seven questionnaires and…
12	2. Materials and Methods — 2.7. Genomic Data and Polygenic Risk Scores (PRS)	The genotyping, imputation, and quality control of COGA genomic data have been described previously…
13	2. Materials and Methods — 2.7. Genomic Data and Polygenic Risk Scores (PRS)	We created PRS using PRS-CSx [63,64,65,66,67], which is a recent, validated method for…
14	2. Materials and Methods — 2.8. Feature selection of EEG Functional Connectivity Variables	In keeping with recent machine learning approaches, including our previous study [69], we used a…
15	2. Materials and Methods — 2.9. Random Forests Classification Model and Parameters	The random forests classification analysis was performed using the R-packages “randomForest”…
16	3. Results — 3.1. Feature Selection of EEG Functional Connectivity Variables	The input data for the feature selection included a total of 330 EEG functional connectivity…
17	3. Results — 3.2. Random Forests Classification Accuracy	The overall prediction accuracy of the random forests model when classifying the memory and control…
18	3. Results — 3.3. Top Significant Features Contributed to the Classification	Out of the 72 input variables of the Random Forest model (see Materials and Methods section of the…
19	3. Results — 3.3. Top Significant Features Contributed to the Classification	The multi-way importance plot (Figure 1) displays all of the significant variables (labeled and…

Name	Type
abstinence	phenotype
Abstinent AUD individuals local	cohort
ACC	anatomy
African American	cohort
alcohol	phenotype
alcohol dependence	phenotype
Alcohol-induced memory problems local	phenotype
Alcohol-Induced Memory Problems local	phenotype
alcohol-related health consequences local	phenotype
Alcohol-related health consequences local	phenotype
Alcohol-related health problems local	phenotype
alcohol-related items local	drug
Alcohol-related memory impairment local	phenotype
alcohol-related memory problems local	phenotype
Alcohol-related memory problems local	phenotype
Alcohol-related neurocognitive outcome local	phenotype
alcohol-related outcomes	phenotype
alcohol-related phenotypes	phenotype
alcohol-related problems	phenotype
Alcohol Use Disorder	phenotype
alcohol withdrawal	phenotype
alpha	anatomy
alpha band	phenotype
alpha band connections local	phenotype
Alzheimer’s disease	phenotype
anterior cingulate cortex	anatomy
Anti-social personality disorder	phenotype
apoE	gene
APOE-4 carriers	cohort
attention deficit hyperactivity disorder	phenotype
attention network	anatomy
AUD	phenotype
AUD individuals local	cohort
AUDIT-C	phenotype
AUD-PRS local	variant
autism spectrum disorder	phenotype
autism spectrum disorders	phenotype
Beta	drug
beta band	phenotype
beta band connections local	phenotype
Beta oscillations local	anatomy
brain damage	phenotype
brain networks	anatomy
Brain stimulation local	drug
brain structure	anatomy
Chronic and Heavy Drinkers local	cohort
Chronic hazardous alcohol consumption local	phenotype
cognition	phenotype
Cognitive behavior therapy local	drug
cognitive phenotypes	phenotype
cognitive processes	phenotype
Cognitive remediation local	drug
Collaborative Study on the Genetics of Alcoholism (COGA)	cohort
Comparative controls local	cohort
comparison group	cohort
consumption-related PRS local	variant
control	cohort
control group	cohort
Control group local	phenotype
control individuals	cohort
controls	cohort
control subjects	cohort
Coping abilities local	phenotype
cortex	anatomy
Cortical-hippocampal network local	anatomy
default mode network	anatomy
default mode network connections local	anatomy
Delta local	drug
delta band	phenotype
dementia	phenotype
depression	phenotype
DHU local	drug
Digit-symbol coding local	phenotype
drinks per week	phenotype
DSM-5 AUD	phenotype
DSM-5 diagnostic criteria local	phenotype
DSM-IV alcohol dependence	phenotype
Dysregulated brain connectivity local	phenotype
EEG	phenotype
EEG functional connectivity variable local	drug
eLORETA	drug
entorhinal cortex	anatomy
episodic memory	phenotype
European ancestry	cohort
Fornix	anatomy
functional connectivity	phenotype
Gamma	drug
gamma band	phenotype
gamma band connections local	phenotype
Gamma oscillations local	anatomy
harm avoidance	phenotype
hazardous alcohol consumption local	phenotype
health consequences	phenotype
health issues	phenotype
health problems	phenotype
Healthy Aging local	cohort
healthy controls	cohort
heavy drinking	phenotype
Hippocampal atrophy	phenotype
Hippocampal–cortical connections local	anatomy
Hippocampal-cortical network local	anatomy
hippocampal formation	anatomy
Hippocampal-prefrontal network	anatomy
hippocampus	anatomy
human alcoholics	phenotype
Hyperconnectivity local	phenotype
Hypoconnectivity local	phenotype
inferior parietal lobe	anatomy
inferior parietal lobule	anatomy
internalizing disorders	phenotype
Internalizing outcomes local	phenotype
IPL	anatomy
Largest number of drinks in a day local	drug
Largest number of drinks within 24 h local	phenotype
learning and memory	phenotype
left temporal cortex	anatomy
light drinkers	phenotype
L.IPL local	anatomy
L.LTC local	anatomy
Logical memory local	phenotype
low-frequency connections (delta band) local	phenotype
L.PCC local	anatomy
L.PFC local	anatomy
L.PHG local	anatomy
major depressive disorder	phenotype
maximum drinks	phenotype
Maximum Habitual Alcohol Intake	phenotype
medial temporal regions	anatomy
memory	phenotype
memory group local	cohort
Memory group local	cohort
Memory individuals local	cohort
memory network local	anatomy
Memory phenotype local	phenotype
memory problems	phenotype
Memory status during baseline local	phenotype
Microstructural alterations local	phenotype
mood regulation	phenotype
MVP	cohort
Negative experiences local	phenotype
Negative experiences related to alcohol consumption local	phenotype
negative mood states local	phenotype
NEO local	drug
neocortex	anatomy
Neural Signatures local	phenotype
Neuromodulation therapies local	drug
neuropsychiatric disorders	phenotype
neuroticism	phenotype
opiate pathways local	drug
P300 measures	phenotype
Parahippocampal–cortical network local	anatomy
parahippocampal gyrus	anatomy
participants	cohort
Past negative experiences local	phenotype
PCC	anatomy
Personality and life experience local	phenotype
personality and life experience factors local	phenotype
PFC	anatomy
PGC	cohort
polygenic risk score	cohort
Polygenic risk score for Alcohol Use Disorder local	variant
Positive experiences local	phenotype
posterior cingulate cortex	anatomy
prefrontal cortex	anatomy
PRS	drug
PRS for AUD local	variant
psychoactive substances	drug
R.ACC local	anatomy
relapse	phenotype
repetitive transcranial magnetic stimulation	drug
Right posterior cingulate cortex local	anatomy
R.LTC local	anatomy
R.PCC local	anatomy
R.PFC local	anatomy
R.PHG local	anatomy
schizophrenia	phenotype
serotonin	drug
Specific Learning Disorder local	phenotype
Specific learning disorders local	phenotype
stress	phenotype
Study groups local	cohort
substance use	phenotype
SUD	phenotype
theta band	phenotype
theta band connections local	phenotype
TPQ local	drug
Traumatic axonal injury local	phenotype
uplift experience local	phenotype
uplift experiences local	phenotype
Uplifting experiences local	phenotype
verbal fluency	phenotype
verbal memory	phenotype
vocabulary	phenotype
withdrawal	phenotype
working memory	phenotype

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