title: Combinations of single nucleotide polymorphisms in neuroendocrine effector and receptor genes predict chronic fatigue syndrome.
abstract: OBJECTIVE
  This paper asks whether the presence of chronic fatigue syndrome (CFS) can be more accurately predicted from single nucleotide polymorphism (SNP) profiles than would occur by chance.
  
  
  METHODS
  Specifically, given SNP profiles for 43 CFS patients, together with 58 controls, we used an enumerative search to identify an ensemble of conjunctive rules that predict whether a patient has CFS.
  
  
  RESULTS
  The accuracy of the rules reached 76.3%, with the highest accuracy rules yielding 49 true negatives, 15 false negatives, 28 true positives and nine false positives (odds ratio [OR] 8.94, p < 0.0001). Analysis of the SNPs used most frequently in the overall ensemble of rules gave rise to a list of 'most important SNPs', which was not identical to the list of 'most differentiating SNPs' that one would calculate via studying each SNP independently. The top three genes containing the SNPs accounting for the highest accumulated importances were neuronal tryptophan hydroxylase (TPH2), catechol-O-methyltransferase (COMT) and nuclear receptor subfamily 3, group C, member 1 glucocorticoid receptor (NR3C1).
  
  
  CONCLUSIONS
  The fact that only 28 out of several million possible SNPs predict whether a person has CFS with 76% accuracy indicates that CFS has a genetic component that may help to explain some aspects of the illness.
authors.affiliation: Virginia Tech, National Capital Region, Arlington, VA, USA. ben@goertzel.org
authors.forename: Benjamin N
authors.initials: BN
authors.lastname: Goertzel
authors.forename: Cassio
authors.initials: C
authors.lastname: Pennachin
authors.forename: Lucio
authors.initials: L
authors.lastname: de Souza Coelho
authors.forename: Brian
authors.initials: B
authors.lastname: Gurbaxani
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Maloney
authors.forename: James F
authors.initials: JF
authors.lastname: Jones
mesh_terms: D000465:Algorithms; D000483:Alleles; D002394:Catechol O-Methyltransferase / Q000235:genetics; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D030541:Databases, Genetic; D015673:Fatigue Syndrome, Chronic / Q000145:classification / Q000453:epidemiology* / Q000235:genetics*; D005787:Gene Frequency; D006801:Humans; D009490:Neurosecretory Systems / Q000502:physiology*; D018377:Neurotransmitter Agents / Q000235:genetics* / Q000502:physiology*; D016017:Odds Ratio; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011956:Receptors, Cell Surface / Q000235:genetics*; D011965:Receptors, Glucocorticoid / Q000235:genetics; D014365:Tryptophan Hydroxylase / Q000235:genetics
chemical_list: C497713:NR3C1 protein, human; D018377:Neurotransmitter Agents; D011956:Receptors, Cell Surface; D011965:Receptors, Glucocorticoid; C494784:TPH2 protein, human; D014365:Tryptophan Hydroxylase; D002394:Catechol O-Methyltransferase